Projets

Les opérations d’influence en ligne exploitent massivement des “bots” pour amplifier la portée et la vitesse de propagation de contenus malveillants, polarisant ou faux et ainsi saturer l’espace informationnel pour dégrader la perception de la société par l’opinion publique. Certains agissent aussi pour confiner des contenus d’information ou d’intérêt général. Ce phénomène est appelé à s’intensifier : les bots constituent, en 2025, plus de 20% des comptes sur les réseaux sociaux et interviennent dans la diffusion de la majorité des messages. Au-delà de la production de contenus (texte, image, vidéo, etc.) permise par l’émergence de l’IA générative, ils deviennent de plus en plus intelligents, capables d’imiter finement des comportements humains et d’agir de manière collective et coordonnée, maximisant artificiellement la visibilité de certains “seeds” narratifs au profit d’acteurs pas toujours bienveillants et minimisant des contre-narratifs éclairants. Pour pouvoir résister à ces influences, dont le plus souvent nous ne connaissons ni les auteurs, ni les origines, ni les intérêts directs et ni les algorithmes qui orchestrent leur propagation et qui évoluent rapidement, il nous paraît indispensable de passer d’une approche sémantique et de type “fact-checking” qui analyse le contenu de l’information, souvent utilisée aujourd’hui, à une approche et des modélisations centrées sur la topologie et la dynamique de la propagation. Il s’agit donc de représenter dynamiquement le segment de réseau ciblé (thématique, géographique, etc.) pour ensuite, identifier et qualifier les “bots ou proxys” ou entités inauthentiques qui perturbent, en amplification ou en confinement, les propagations de contenus. La qualification s’effectuant essentiellement sur l’analyse de “patterns” de propagation individuelle ou collective. Grâce à ces “patterns”, il devient possible de qualifier le comportement des entités inauthentiques (individuel, sur le réseau, au sein de son écosystème artificiel) afin d’adapter la riposte pour contrecarrer ou minimiser leur impact. Des actions de minimisation de la viralité de ces bots peuvent être mises en œuvre directement au sein du réseau de propagation ou indirectement par l’action induite auprès des lecteurs pour résister aux influences artificielles. Dans le champ de la défense nationale, le projet s’inscrit dans la continuité des efforts entrepris par la DGA, le SGDSN et la VIGINUM pour renforcer la résilience informationnelle et la capacité de détection et de riposte face aux ingérences numériques étrangères. Depuis la création de la VIGINUM (2021) et l’institutionnalisation de la fonction stratégique « Influence » dans la Revue nationale stratégique 2022, la France reconnaît le champ informationnel comme un espace de confrontation à part entière. Le projet prolonge cette dynamique en proposant une approche scientifique, technologique et sociotechnique visant à outiller la détection, la caractérisation et surtout la minimisation opératoire des phénomènes de manipulation. Contrairement aux dispositifs purement analytiques, le projet aborde la boucle complète de l’action – de la détection algorithmique à la mise en information des usagers, à la mesure de l’efficacité cognitive et sociale des dispositifs de signalement et à la manipulation de la topologie de diffusion inauthentique. Cette articulation entre évaluation scientifique, utilisabilité, et acceptabilité opérationnelle répond directement aux priorités fixées par le rapport parlementaire Opérationnalisation de la fonction stratégique Influence (Assemblée nationale, 2025), qui recommande de développer des outils « responsables, auditables et centrés sur la confiance publique ». Le projet TALOS - Apprentissage adaptatif aux menaces pour contrer les bots - propose ainsi de lutter contre la manipulation artificielle de l’information sur les médias sociaux à l’aide de signalement et de modération automatique de la diffusion des comptes inauthentiques.

Le projet CYANOCAT étudie un processus biominéralogique découvert récemment, par lequel des cyanobactéries d’eau douce précipitent, en se divisant, des anneaux d’oxydes de fer et de manganèse. Pouvant atteindre des densités cellulaires élevées, ces bactéries produisent de grandes quantités d’anneaux. Ce mécanisme pourrait être une voie méconnue mais importante de piégeage et de recyclage des métaux. En concentrant le Fe et le Mn — deux éléments essentiels mais parfois limitants ou toxiques pour les bactéries, notamment photosynthétiques — ces cyanobactéries pourraient moduler la disponibilité du Fe–Mn, la chimie du carbone organique dissous ou encore la dynamique des métaux traces dans les milieux d’eau douce. Cependant, la distribution phylogénétique de ces bactéries, leur prévalence, les mécanismes moléculaires du processus — en particulier de concentration du Fe dans des conditions où il est supposé peu disponible — ainsi que son impact biogéochimique restent inconnus. CYANOCAT développera une approche intégrée associant géochimie, minéralogie et génomique, pour (i) déterminer la distribution phylogénétique et environnementale de ces cyanobactéries, (ii) identifier les gènes et voies métaboliques impliqués dans la biominéralisation, (iii) quantifier leur contribution aux cycles locaux du Fe, du Mn et des métaux traces. Un consortium pluridisciplinaire associant spécialistes en géochimie/minéralogie (IMPMC, LSCE) et écologie microbienne/génomique (MCAM, ESE) mènera des campagnes de terrain pour analyser les colonnes d’eau et sédiments de plusieurs lacs. Une large gamme d’outils sera mobilisée : cytométrie en flux, microscopies, analyses synchrotron, génomique comparative, métabarcoding et cultures. En révélant un maillon manquant du cycle des métaux dans les eaux douces, CYANOCAT pourrait redéfinir notre compréhension du fonctionnement géochimique de certains lacs et identifier une nouvelle stratégie microbienne de séquestration et d’utilisation des métaux.

Le projet ItacoMac vise à décrypter le rôle du métabolite itaconate, produit par l’enzyme ACOD1/IRG1, dans la régulation de la fonction des macrophages et le maintien de l’homéostasie du tissu adipeux. Dans l’obésité et le diabète de type 2, les macrophages du tissu adipeux (ATM) soutiennent une inflammation chronique de bas grade qui altère profondément l’équilibre métabolique. Des analyses unicellulaires récentes, notamment issues de notre consortium, ont révélé une hétérogénéité fonctionnelle marquée, avec l’identification de sous-populations spécialisées : les macrophages résidents LYVE1? TIM4?, garants de la stabilité tissulaire ; les macrophages lipidiques TREM2? (LAM), impliqués dans la clairance des adipocytes apoptotiques ; et les macrophages septaux LYVE1? CD209b?, qui contrôlent le devenir des progéniteurs adipocytaires via la signalisation TGFß1. Toutefois, les mécanismes métaboliques qui coordonnent ces populations et assurent leur équilibre fonctionnel restent largement inconnus. Nos données préliminaires identifient ACOD1/itaconate comme un point de contrôle central de cette régulation : Acod1 est fortement exprimé dans les macrophages résidents LYVE1?, et la production d’itaconate est augmentée en condition d’obésité. De plus, la délétion spécifique d’Acod1 dans les macrophages TIM4? exacerbe le remodelage du tissu adipeux et favorise l’expansion des macrophages septaux, suggérant que l’itaconate limite la plasticité macrophagique délétère et contribue à contenir l’inflammation. Pour tester cette hypothèse, ItacoMac combinera des modèles murins conditionnels, des approches de multiomique unicellulaire et spatiale, de la métabolomique ciblée et un phénotypage métabolique avancé afin de cartographier la dynamique de l’itaconate et d’en définir les fonctions dans la gestion lipidique, le contrôle de l’inflammasome et la thermogenèse. En établissant comment ce métabolite orchestre la spécialisation macrophagique et l’adaptation du tissu adipeux, ItacoMac apportera un cadre mécanistique inédit reliant immunométabolisme, stress oxydant et thermogenèse, et positionnera l’axe ACOD1/itaconate comme un déterminant clé de la santé métabolique et des pathologies associées à l’obésité.

HOSTLINK explore un nouveau mécanisme de communication moléculaire entre parasites et hôtes, au cœur d’une maladie qui touche plus de 280 millions de personnes dans le monde: la schistosomiase. Ces vers plats utilisent des récepteurs originaux, appelés Venus Kinase Receptors (VKR), essentiels à leur reproduction mais absents des vertébrés – donc de l’être humain. Notre équipe a récemment élucidé la structure tridimensionnelle de la schistosomine, une petite protéine sécrétée par les escargots hôtes et obtenue par synthèse totale, et montré qu’elle agit comme un interrupteur moléculaire d’une manière inattendue : au lieu d’interagir avec le domaine extracellulaire, elle traverse la membrane cellulaire pour se fixer directement sur le cœur catalytique du récepteur et en moduler l’activité. Cette communication croisée entre espèces suggère que les parasites peuvent détourner des signaux neuroendocriniens de leurs hôtes pour soutenir leur développement. En combinant chimie des protéines, biologie structurale, analyses fonctionnelles (cellules Bge, ovocytes de xénope) et cycles d’infection complets maintenus chez nos partenaires, HOSTLINK identifiera les déterminants de compatibilité entre mollusques et schistosomes et recherchera de nouvelles séquences de schistosomines et de VKR issues d’espèces sauvages afin de retracer leur co-évolution. Nous testerons la spécificité versus la réactivité croisée des couples schistosomine–VKR dans plusieurs paires mollusque–parasite, en reliant structures, activité kinase et phénotypes de développement (GVBD et phosphorylation MAPK/AKT). Au-delà de la parasitologie, en révélant un mécanisme unique de régulation de récepteurs tyrosine-kinases, le projet pourrait inspirer de nouvelles stratégies antiparasitaires et guider la conception de modulateurs visant d’autres RTK impliquées dans des maladies humaines (par ex. cancers, inflammation, régénération tissulaire).

Les plantes de la famille des légumineuses développent des organes spécialisés d’acquisition des nutriments, notamment les nodules fixateurs d’azote et, chez certaines espèces comme le lupin blanc (Lupinus albus), des racines protéoïdes favorisant l’acquisition du phosphore. La formation de ces organes, fortement coûteuse en carbone, est finement régulée par des signaux systémiques intégrant l’état nutritionnel de la plante à l’échelle de l’organisme entier. Chez Medicago truncatula, ces régulations reposent sur deux modules antagonistes bien caractérisés : les peptides CLE, perçus par le récepteur SUNN, inhibent la nodulation, tandis que les peptides CEP, perçus par le récepteur CRA2, la stimulent en condition de carence azotée. Cependant, ces modèles restent largement centrés sur la nodulation et prennent peu en compte les réponses au phosphore et le développement racinaire, ni les étapes de maturation des peptides de signalisation. Chez le lupin blanc, nous avons récemment mis en évidence une voie systémique « élargie », appelée AoDev (« Autoregulation of Development »), contrôlant conjointement la formation des nodules et des racines protéoïdes via le récepteur CCR1. Cette découverte révèle un mécanisme de régulation intégrée reliant les réponses à l’azote et au phosphore. L’identification d’un second mutant, ccr2, affecté dans un gène codant une prolyl-4-hydroxylase (P4H), suggère l’existence d’un niveau de régulation inédit impliquant des modifications post-traductionnelles de peptides de signalisation. Cette étape constitue aujourd’hui une lacune majeure dans la compréhension des voies systémiques, aucune enzyme responsable de l’hydroxylation des peptides n’ayant été fonctionnellement caractérisée à ce jour chez les plantes. Le projet LEG-SYS vise à lever ce verrou en proposant une analyse intégrée des régulations systémiques du développement racinaire chez les légumineuses. Il repose sur trois hypothèses centrales : (i) la voie AoDev intègre des modules antagonistes de type CLE/CCR1 et CEP/CRA2, (ii) CCR2 contrôle la maturation des peptides via l’hydroxylation de résidus proline, constituant une nouvelle étape enzymatique de régulation des signaux peptidiques agissant à longue distance, et (iii) des voies impliquant des récepteurs CRA2/CRA2-like contribuent à l’intégration des signaux azote/phosphore. Pour tester ces hypothèses, le projet LEG-SYS combine des approches de génétique, biochimie des peptides, transcriptomique, et physiologie des régulations systémiques, dans deux espèces de légumineuses complémentaires, le lupin blanc et Medicago truncatula. L’organisation en quatre « Work Packages » permettra d’identifier les peptides impliqués, de caractériser cette nouvelle enzyme de maturation post-traductionnelle, d’analyser les récepteurs associés, et d’intégrer ces éléments dans un modèle de régulation systémique unifié. En établissant pour la première fois un cadre mécanistique reliant maturation des peptides, perception et régulation développementale, le projet LEG-SYS ambitionne de dépasser les modèles actuels centrés sur la nodulation pour proposer une vision intégrée du contrôle systémique du développement racinaire en réponse à différents nutriments. Ces avancées fourniront des bases conceptuelles nouvelles pour comprendre la plasticité racinaire et, à terme, améliorer l’efficacité d’utilisation des nutriments dans un contexte agroécologique.

NeBeMIMO s'attaque à un verrou critique pour les réseaux mobiles 6G : la détection en temps réel des canaux en champ proche dans les systèmes MIMO à très grande échelle (XL-MIMO). Les futurs réseaux 6G fonctionneront à des fréquences plus élevées avec des réseaux d'antennes extrêmement grands, ce qui rendra les communications en champ proche courantes. Les méthodes actuelles qui reposent sur l'apprentissage séquentiel des faisceaux et des hypothèses de champ lointain sont inefficaces, en particulier dans les bandes millimétriques et sub-THz, à cause du besoin élevé de signaux pilotes, d’une précision limitée et d’une forte sensibilité au rapport signal à bruit. NeBeMIMO propose une approche radicalement nouvelle en exploitant le balayage de faisceau dépendant de la fréquence des antennes passives à ondes de fuites dans le champ proche. En tirant parti de la dépendance unique des fronts d'onde sphériques à l'angle et à la distance, le projet permet l'estimation en temps réel de l'emplacement des utilisateurs et des diffuseurs à l'aide de signaux de référence montants, éliminant ainsi le balayage coûteux des faisceaux et la surcharge de signaux pilotes. Cette approche intègre de la conception d’antennes et du traitement d usignal avancés afin d’estimer conjointement les direction angulaires et les distances.

Pour la plupart des systèmes contrôlés, seule une partie de l’état -la sortie- peut être mesurée en ligne par des capteurs physiques. Cependant, estimer l’état complet du système est crucial pour des objectifs de surveillance, de détection d’erreur, ou de bouclage de sortie. Les observateurs sont des estimateurs en ligne synthétisés pour cette tâche. Leur convergence et leur efficacité dépendent de l’observabilité du système, c’est-à-dire de la capacité à estimer les inconnues à partir des mesures. Mais pour les systèmes non-linéaires, l’observabilité dépend de la commande. Cette dépendance peut être exploitée positivement pour résoudre des problèmes d’estimation en excitant le système avec une commande appropriée pour assurer l’observabilité. Cette approche correspond à une stratégie dite «active sensing». Cependant, elle constitue aussi une source de difficulté majeure pour la commande par bouclage de sortie. Dans ce contexte, une stratégie classique consiste à synthétiser une loi de commande par retour d’état et à la combiner avec l’estimation fournie par un observateur. Mais pour les systèmes non-linéaires, on se heurte à des cas où contrôle et observation sont concurrents, car la loi de commande à l’état stationnaire rend le système inobservable. Dans ce cas, tandis que l’objectif de contrôle se réalise, l’observateur devient incapable d’estimer correctement l’état, ce qui détériore en retour la commande. Cette compétition peut être interprétée comme un dilemme «exploration - exploitation», où la commande doit à la fois exploiter l’estimation et exciter le système pour l’améliorer. L’objectif de ce projet est double: -Fournir une méthodologie systématique, pratique, et avec des garanties théoriques, pour concevoir des commandes assurant une convergence rapide et précise de l’observateur. -Synthétiser des stratégies de bouclage de sortie qui permettent de surmonter les difficultés apparaissant lorsque contrôle et observation sont des objectifs concurrents.

Comment limiter les effets des activités humaines sur le système Terre ? Ce sujet n'est pas nouveau, mais l’accélération de ces phénomènes dans un contexte de changement global nécessite une prise de conscience collective. Parmi les 9 limites planétaires identifiées qui pourraient mettre en danger l’existence de l’Homme si des seuils sont dépassés, on retrouve l’émission des entités nouvelles (produits chimiques, biologiques, (nano)matériaux manufacturés et sous-produits de transformation) dans notre Environnement. La définition d’une limite planétaire pour l’émission des entités nouvelles est quasi-impossible car on ne peut définir une limite d’(éco)toxicité pour la totalité. MAGICIA a pour objectif de développer une approche robuste visant à améliorer notre capacité d’évaluation à haut débit des risques environnementaux associés aux nouvelles entités sur le long-terme dans un contexte de changement climatique. Le 1er défi sera de développe des tests fonctionnels à haut débit afin d’étudier l’exposition environnementales aux entités nouvelles. Pour cela nous éluciderons de façon découplée (i) les mécanismes bio-physico-chimiques et cinétiques réactionnelles aux interface vivant/minéral/nouvelles entités, et (ii) les processus de génération d’entité (nano)particulaires au cours du cycle de vie des matériaux avancés. Nous créerons des bancs d’analyses micro-fluidiques associant divers outils de spectrométrie, spectroscopie et imagerie. Le 2e défi sera d’utiliser l’Intelligence artificielle pour développer des jumeaux numériques des mésocosmes pour prédire les risques associés aux mélanges complexes d’entités nouvelles sur long-terme en contexte de changement climatique. Nous nous appuierons sur des bases de données d’exposition, des modèles de transport et de géochimie. Nous évaluerons la robustesse de notre approche en menant une expérimentation en mésocosmes aquatiques mimant la contamination d’un écosystème lenthique à un mélange complexes de nouvelles entités.

Les assemblages géométriquement frustrés (Geometrically Frustrated Assemblies, GFA) couvrent de nombreux domaines des sciences, tels que le magnétisme, le repliement des protéines ou les cristaux liquides. Les GFA apparaissent lorsque des interactions concurrentes empêchent le système d’adopter des arrangements simples, conduisant à l’émergence de propriétés structurelles et multifonctionnelles originales. À l’inverse, les matériaux colloïdaux synthétiques présentent généralement peu ou pas de frustration, donnant lieu à des structures simples, compactes et statiques. Ce projet vise à concevoir et à manipuler des assemblages frustrés de nanoparticules (NPs) inorganiques colloïdales afin de former des matériaux complexes et fonctionnels directement en solution. Le premier objectif du programme de recherche est d’exploiter les principes des GFA entre des nanoparticules ne se conformant pas aux pavages standards, afin d’accéder à une nouvelle gamme de symétries originale. Le second objectif est de doter ces assemblages d’une réponse structurale dynamique à des stimuli externes, permettant un contrôle actif de leurs propriétés et fonctionnalités. Le programme de travail se concentre sur la conception rationnelle de nanostructures périodiques bidimensionnelles constituées de nanobâtonnets orientés (désignées sous le terme de métasurfaces) et s’articule autour de trois objectifs (O) : (O1) l’ingénierie d’assemblages géométriquement frustrés par la conception de nanobâtonnets présentant des sections polygonales originales (par exemple pentagonales ou chirales), ainsi que par l’assemblage de réseaux binaires ; (O2) le contrôle des paramètres de réseau des métasurfaces (distance inter-particulaire et symétrie) par des moyens chimiques ainsi que par l’application de champs externes ; (O3) l’étude des propriétés optiques dynamiques des métasurfaces frustrées. De subtiles modifications des interactions colloïdales en solution induiront des changements structuraux remarquables, tels que des ruptures de symétrie, une porosité modulable et l’apparition d’aperiodicité. Cette nouvelle classe de matériaux s’inspire d’autres systèmes reposant sur les GFA, tout en présentant des « métapropriétés » optiques absentes dans la nature, telles que des interactions lumière–matière renforcées et une activité chiroptique intense. Dans l’ensemble, les métasurfaces frustrées permettront la découverte de structures uniques et dynamiques, ouvrant la voie à de nouvelles applications en plasmonique et au-delà.

La structure de bande électronique détermine les propriétés électroniques d’un matériau. Ainsi, pour comprendre un nouvel état de la matière, il est essentiel d’accéder à la structure de bande électronique du matériau. Un phénomène particulièrement intéressant est l’effet Hall quantique anormal (QAHE), dans lequel la résistance transversale du matériau est quantifiée en l’absence de champ magnétique. Cet effet a été proposé pour améliorer les interconnexions entre dispositifs quantiques, héberger des modes de Majorana en proximité avec des supraconducteurs, et servir de standard de résistance quantique de Hall sans champ magnétique. Le QAHE est observé dans divers types de matériaux (comme les isolants topologiques, les systèmes de moiré, etc.), à condition que le système brise la symétrie de renversement du temps et possède des bandes topologiques non triviales. Les matériaux à base de graphène avec des motifs de moiré sont particulièrement attractifs pour étudier le QAHE en raison de leur meilleure qualité cristalline, de leurs contacts électriques plus performants que ceux d’autres matériaux, de leur grande ajustabilité et du contrôle in situ de l’alignement des couches. Malheureusement, l’accès expérimental à leur structure de bande électronique est complexe, car ces matériaux sont encapsulés et de taille limitée, ce qui empêche l’utilisation des outils de spectroscopie standard. Je propose de mettre en œuvre une technique de spectroscopie tunnel résolue en énergie et en moment (MERTS), combinée à des mesures de transport de charge et à un contrôle angulaire in situ, afin d’explorer l’origine de l’effet Hall quantique anormal dans les systèmes de moiré à base de graphène. Cette approche tripartite me permettra de corréler directement les caractéristiques de la fonction spectrale et les propriétés de transport de charge à mesure que la longueur d’onde du moiré évolue, et d’aborder les questions suivantes : i) Est-il possible d’observer la fonction spectrale des matériaux 2D à l’aide de la MERTS ? ii) Quel est le lien entre l’alignement des couches (brisant la symétrie) et la topologie des bandes ? Ces résultats traceront une voie pratique pour étudier et concevoir des bandes topologiques dans d’autres matériaux 2D et hétérostructures.

Les microalgues photosynthétiques peuvent être considérées comme de petites usines biologiques capables de produire des aliments, des aliments pour animaux et des biomolécules à haute valeur ajoutée. Leur culture présente des bénéfices environnementaux : cyclage du dioxyde de carbone, dépollution des eaux et valorisation potentielle en tant que biocarburant. Enfin, elles peuvent être cultivées sur des terres non arables, évitant ainsi toute concurrence avec les cultures alimentaires actuelles. La faible disponibilité de la lumière naturelle limite la production industrielle de microalgues photosynthétiques. Deux stratégies d’atténuation sont actuellement mises en œuvre : - le déploiement de photobioréacteurs sur de grandes surfaces afin de capter un maximum de lumière solaire, au prix d’investissements en capital élevés ; - le recours à l’éclairage artificiel, entraînant des coûts d’exploitation électriques importants. Ce projet propose un nouveau paradigme : collecter et concentrer la lumière solaire à l’aide de miroirs peu coûteux avant de rediriger cette lumière ultra-intense sur la culture. Elle se concrétisera par un nouveau procédé intensifié conduisant à une photosynthèse augmentée à grande échelle. Néanmoins, une lumière ultra-intense est connue pour être délétère pour les cellules si elle n’est pas délivrée de manière appropriée. En nous appuyant sur une preuve de concept déjà établie, nos travaux exploreront le territoire encore inexploré de la photosynthèse sous lumière ultra-intense (jusqu’à plus de dix fois la puissance du soleil). Pour relever ce défi, nous utiliserons en synergie des techniques expérimentales et de modélisation de pointe. D’un point de vue scientifique, nous anticipons des résultats sans précédent conduisant à de nouvelles connaissances à trois niveaux : l’appareil photosynthétique, la cellule et le bioprocédé. À l’aide d’outils numériques interdisciplinaires, nous élaborerons des modèles s’appuyant sur les connaissances générées et guidant notre exploration. D’un point de vue applicatif, nous concevrons et réaliserons la première génération de photobioréacteurs à lumière ultra-intense, permettant de dépasser la limitation énergétique actuelle de la photosynthèse. Ils démontreront la pertinence du procédé en atteignant des performances inédites en matière de production de microalgues et de biomolécules.

DADASTORM vise à lever un verrou majeur de la science du climat: attribuer de manière robuste au changement climatique les systèmes convectifs de méso-échelle (MCS) et leurs aléas associés (pluies intenses, grêle, foudre, rafales destructrices, tornades), en particulier en Europe et en Méditerranée. Malgré un consensus sur l’augmentation de l’humidité atmosphérique et de l’instabilité avec le réchauffement global, le rôle de la variabilité climatique naturelle dans la mise en place des configurations atmosphériques de grande échelle favorables à l’initiation et à l’organisation de la convection reste mal quantifié. Cette incertitude, combinée aux limites des observations et des modèles climatiques pour représenter la convection organisée, empêche aujourd’hui l’attribution fiable d’événements MCS individuels, contrairement à d’autres extrêmes météorologiques. Le projet repose sur une approche intégrée combinant détection, émulation, attribution et simulation d’aléas. Le premier objectif est de reconstruire un ensemble cohérent de trajectoires et de caractéristiques de MCS à partir de données satellitaires et observationnelles haute résolution depuis 2000, afin de relier occurrence, organisation et intensité des MCS aux conditions atmosphériques de grande échelle et aux aléas associés. Ces relations serviront de base pour étendre l’information jusqu’à 1950 en exploitant les réanalyses climatiques, des méthodes de détection avancées fondées sur l’apprentissage non supervisé et les analogues, ainsi que des bases d’impacts pour contraindre les événements les plus extrêmes. Le deuxième objectif est d’adapter les méthodes d’attribution conditionnelle existantes, basées sur des analogues de circulation atmosphérique, à des phénomènes convectifs fortement spatialisés et transitoires. DADASTORM identifiera les variables climatiques horizontales et verticales les plus pertinentes (géopotentiel, humidité, instabilité, profils de vent et de température) et intégrera des approches causales afin de distinguer l’influence des forçages anthropiques (gaz à effet de serre, aérosols) de celle de la variabilité naturelle sur l’occurrence et l’intensité des MCS. Des études de cas récentes en Europe et en Méditerranée seront menées en interaction avec des acteurs institutionnels et socio-économiques. Enfin, le projet développera un émulateur de trajectoires synthétiques de MCS couplé à un simulateur open source d’aléas convectifs. Ce dispositif permettra d’augmenter fortement les ensembles d’événements à l’échelle climatique et de générer, pour chaque trajectoire, des ensembles probabilistes de pluies intenses, grêle, foudre, rafales et tornades à partir de données dédiées et de modèles statistiques ou neuronaux. En combinant systèmes dynamiques, apprentissage automatique informé par la physique et attribution climatique, DADASTORM comblera une lacune critique en rendant possible l’attribution des aléas liés aux MCS au changement climatique. Les jeux de données et outils développés seront ouverts et transférables, avec des retombées directes pour la recherche, l’évaluation des risques, les politiques d’adaptation et la communication scientifique sur les impacts du réchauffement climatique.

Les communautés d'Afrique de l'Ouest sont confrontées à des défis majeurs en matière d'accès à l'énergie, de gestion des déchets et de sécurité alimentaire. Ce projet, REMIX-3P, propose un système intégré de trigénération hors réseau combinant biogaz, énergie solaire photovoltaïque et énergie solaire concentrée pour fournir de l'électricité, du refroidissement, du séchage et du chauffage. Le système s'attaque à la pauvreté énergétique en concevant une plateforme durable et peu coûteuse qui recycle les déchets organiques en biogaz, régénère les batteries en fin de vie, remet en état les modules photovoltaïques et utilise l'énergie solaire pour produire de l'électricité. Les principales innovations comprennent un cycle de Rankine fermé (vapeur provenant du solaire à concentration/biogaz), des modules thermoélectriques pour la récupération de la chaleur des déchets et un double stockage thermique/électrochimique. Le système soutient les utilisations productives : énergie électrique pour les ménages et les équipements à usage productif (100 kW au total), chaîne du froid pour la conservation des aliments (10-20 kW), et séchage à l'air chaud des produits agricoles (10-20 kW thermiques). La puissance et les températures d'entrée et de sortie de chaque sous-système seront ajustées en fonction des données socio-économiques de la communauté cible et des conditions techniques du site. La structure du système sera conçue pour optimiser les transferts d'énergie, limiter les pertes d'exergie, assurer la sécurité et optimiser l'utilisation. Une méthode de dimensionnement modulaire et un modèle commercial garantiront l'évolutivité et l'accessibilité financière. Les études existantes soulignent le potentiel de l'intégration de l'énergie solaire thermique et du biogaz dans les systèmes à cycle de Rankine pour fournir des solutions d'électricité durables aux communautés rurales. Cependant, ces études restent théoriques et ne récupèrent pas la chaleur perdue pour des utilisations telles que le séchage des aliments, qui est essentiel en Afrique de l'Ouest. REMIX-3P comble cette lacune avec un système tout-en-un, intégrant des éléments thermoélectriques et un véritable démonstrateur in situ. Le projet REMIX-3P combine la caractérisation des matériaux (WP1), les études de faisabilité menées par les communautés (WP2), la modélisation du système (WP3), les algorithmes de gestion de l'énergie (WP4) et le déploiement d'un démonstrateur sur site au Bénin (WP5). Les parties prenantes sont les autorités locales, le consortium OZO (régénération des batteries) et les partenaires de recherche de l'UE et de l'UA. Les effets attendus sont la réduction de la pollution (production de biogaz de 20 à 50 m³/jour), l'amélioration de la sécurité alimentaire et la création de revenus grâce aux services énergétiques. La priorité est donnée à l'intégration de la dimension de genre en formant les femmes au fonctionnement du système et en adaptant les solutions énergétiques aux besoins domestiques. Le projet s'aligne sur les objectifs MAR2 (gestion de la fin de vie) et MAR3/4 (systèmes intelligents hors réseau), contribuant ainsi aux objectifs du partenariat UA-UE sur le changement climatique et l'énergie durable.

Le projet AICAtS vise à faire progresser l’intégration de l’intelligence artificielle dans les sciences de l’atmosphère en abordant des défis majeurs d’apprentissage automatique qui limitent la modélisation fiable des phénomènes géophysiques complexes et en validant ces avancées sur des cas d’usage concrets. Ces cas d’usage incluent la prévision météorologique, l’estimation des précipitations et la prévision de la température de bulbe humide. Ils couvrent une variété de situations représentatives nécessitant le développement de nouveaux cadres et méthodologies en IA. Sur le plan méthodologique en IA, le projet se concentrera sur trois défis clés, essentiels au développement de solutions d’apprentissage automatique pour ces cas d’usage et, plus largement, pour la modélisation atmosphérique : modélisation de la stochasticité des processus physiques via des modèles probabilistes génératifs ; généralisation et extrapolation à diverses situations physiques en contexte d’apprentissage avec peu de données ; quantification des incertitudes pour les modèles physiques basés sur les données. Le consortium rassemble des partenaires aux expertises hautement complémentaires : INRIA-ARCHES (ML et climat), ISIR (apprentissage profond pour la physique) et LATMOS (sciences de l’atmosphère). Ces trois équipes ont une solide expérience en recherche multidisciplinaire à l’interface entre climat, environnement et apprentissage automatique. Un des atouts majeurs de cette collaboration réside dans la synergie entre l’IA et les sciences atmosphériques, permettant le développement de modèles d’apprentissage automatique plus avancés et fondés sur des principes physiques. Le projet a un fort impact environnemental. Son importance s’étend à des secteurs critiques tels que l’agriculture, l’énergie et la gestion des catastrophes, où des prévisions améliorées des précipitations et de la température de bulbe humide peuvent optimiser la prise de décision et les stratégies d’atténuation des risques. Le projet fera appel aux très grandes infrastructures de recherche notament sur le calculateur Jean Zay.

L'intelligence artificielle a démontré son immense potentiel en radiologie, en particulier pour l'imagerie par tomodensitométrie (CT). Néanmoins, un défi majeur est le manque de pouvoir de généralisation des modèles d'apprentissage profond standards. Récemment, les modèles de fondation (FM) ont été développés pour le traitement du langage naturel, avec un succès retentissant. Bien que des FM aient également été proposés dans certains domaines spécifiques de l'imagerie médicale, avec des résultats prometteurs, ils sont encore peu explorés, un défi majeur étant la diversité des modalités d'imagerie en médecine. Le projet FM2AI propose de tirer parti des ressources exceptionnelles de l’Entrepôt de Données de Santé de l’Assistance Publique - Hôpitaux de Paris, pour proposer un modèle de fondation ouvert, adapté à l’imagerie 3D CT abdominale, accompagné d’outils logiciels d’apprentissage machine, pour viser une intégration clinique efficace et effective du modèle. Nous concevrons des méthodes robustes d'apprentissage few-shot pour permettre l'adaptation et la généralisation du modèle de fondation à des taches diagnostiques spécifiques, telles que la classification et la segmentation d’images CT abdomino-pelviennes, sans nécessiter d'efforts massifs de réannotation ni de ressources GPU. Nous développerons des techniques originales d'estimation conformelle d'incertitude dans le cadre des prédictions multitâches, afin d'assurer fiabilité, interprétabilité, et confiance des méthodes. Nous validerons l'ensemble du processus sur trois questions cliniques à fort impact soulevées en oncologie abdominale-pelvienne, en coordination avec deux partenaires AP-HP, garantissant une adoption clinique efficace. Pour atteindre ces objectifs ambitieux, le consortium réunit quatre acteurs d'excellence de la région Île-de-France, experts dans tous les domaines concernés, allant des mathématiques appliquées, de l'apprentissage automatique, à la radiologie abdominale-pelvienne, travaillant en synergie.

L'hypoxie au coeur des tumeurs compromet considérablement l'efficacité de la radiothérapie. Or, les nanoparticules radiosensibilisantes actuellement en développement sont trop volumineuses pour diffuser efficacement au sein de la matrice extracellulaire tumorale et atteindre ces zones critiques, ce qui limite leur potentiel radioadjuvant. ReOxy propose de s'affranchir de ces contraintes grâce à une nanoparticule organique de petite taille (d < 20 nm), capable de pénétrer en profondeur dans les tumeurs solides et d’augmenter localement la concentration en dioxygène, potentialisant ainsi l'efficacité tumoricide de la radiothérapie.

3DCAM Sensors développe et industrialise des capteurs compacts de mesure en temps réel des particules chargées en orbite basse. Ces instruments comblent une absence critique de données environnementales, qui laisse les futures constellations européennes exposées à des risques de pannes lors d'événements solaires majeurs. Cette technologie de rupture, affichant des performances 10 fois supérieures à l'état de l'art, est issue d'une thèse cofinancée par le CNES et l'École polytechnique. Identifiée comme prioritaire par la Stratégie Nationale Spatiale, elle sera testée en orbite en 2028.

ADAM (Anomaly detection by adaptative modeling) est un logiciel de maintenance prévisionnelle pour les chaînes de production industrielle. À partir des signaux capteurs et actionneurs déjà présents sur la ligne, il construit et met à jour automatiquement un jumeau numérique comportemental, sans modélisation manuelle ni paramétrage expert. Ce jumeau, basé sur des lois physiques du procédé, prend la forme d'un graphe interprétable. Fidèle au comportement réel de la machine, il détecte les écarts dès leur apparition et permet d'en identifier l'origine, avant qu'ils ne dégradent la production. Conçu pour être plug-and-play et à faible coût d'entrée, ADAM ouvre la maintenance prévisionnelle à des lignes jusqu'ici hors de sa portée et réduit les pertes liées aux arrêts non planifiés.

SMAAI (Signal multi-modal analysis & artificial intelligence) est un projet de startup deeptech dédié à l’analyse intelligente de signaux. L’objectif est de faire pour le signal ce que les grands frameworks de vision par ordinateur ont permis pour l’image : développer des modèles d’intelligence artificielle réutilisables, faciles à entraîner, à déployer et à intégrer dans des applications industrielles, sans reconstruire une chaîne de traitement spécifique à chaque nouveau cas d’usage. SMAAI vise une industrialisation dans des domaines variés tels que le biomédical, la ville intelligente, les capteurs industriels, les moteurs, l’astrophysique ou la géophysique

Phlo est une technologie disruptive dont l’objectif est de multiplier les rendements de la bioproduction. Il s’agit d’une méthode de production qui utilise un couple phage-bactérie, c'est-à-dire un virus et son hôte. Aujourd'hui, les bactéries sont cultivées seules pour produire des molécules notamment thérapeutiques ou cosmétiques. L'ajout des phages permet une forte augmentation de la production tout en supprimant une étape d’extraction, et ce dans les équipements déjà existants. La mission de Phlo est d’aider les industriels de la bioproduction à diminuer les coûts relatifs aux molécules déjà produites, et à produire des molécules innovantes dont les rendements sont aujourd’hui insuffisants pour garantir leur viabilité économique.

Materials under high pressure exhibit exciting topics such as the superconductivity (SC) of hydrogen-rich molecular compounds (super-hydrides) in the long standing search of room-temperature SC. While pressures above 100 GPa can be routinely created in a diamond anvil cell (DAC), the tiny sample volume almost precludes the use of non-optical detection schemes to probe the sample properties. The project idea is to integrate nitrogen-vacancy (NV) centers in the DAC and use the optically detected magnetic resonance (ODMR) of the NV electronic spin to image the Meissner effect. The project relies on our first results where we engineered NV centers on the tip of a diamond anvil and adapted quantum sensing methods to detect pressure-induced magnetic and SC transitions under tens of GPa. By controlling the stress distribution to achieve hydrostatic conditions that preserve the NV symmetry, we have extended this method above 100 GPa, reaching the pressure range of existence of SC in super-hydrides. These materials need to be synthetized at high pressure by laser heating which induces strong inhomogeneities with micron scale. We will use of widefield NV magnetometry to locally image the Meissner effect and the flux trapping in the SC grains whereas the conventional measurements average over the entire DAC geometry and therefore discard all local information. By operating NV sensing on a synchrotron beamline, we will determine the crystal structure of the super-hydrides after the synthesis in the DAC. We will finally couple the spatial detection with noise spectroscopy to measure the temporal current fluctuations in the SC. These methods will be implemented in parallel on Hg-doped cuprates as testbed systems. In a complementary task we will investigate the implementation of NV-based microscale nuclear magnetic resonance in the DAC. Our goal will be to exploit the sensitivity of a dense ensemble of NV centers to detect the chemical shift of the nuclear spins in the sample.

Speckle patterns are distinct features of disordered materials. While often regarded as mere noise, the intricate and responsive speckle patterns to minor fluctuations in external factors render them an ideal candidate for applications in hyperspectral imaging and sensing. The MetaSpectrometer harnesses the high information capacity of the speckle pattern of resonant disordered metasurfaces for compact, machine learning-assisted, non-invasive, and efficient near-infrared spectroscopy. An ultra-compact footprint, portability, cost-efficiency, minimal losses, machine-learning assisted recognition, angle-insensitivity, suppressed specular scatterance, significant memory effect, and ability to accommodate low coherence fields are the main features that cannot be currently obtained with any technology proposed so far and would represent a huge step forward in the state of the art. MetaSpectrometer brings together the complementary expertise of the postdoctoral researcher (PR) in metasurface engineering; the incoming host (CNRS-C2N, France) in silicon photonics, optoelectronics and nanofabrication; the associated the outgoing host (MIT, USA) in spectroscopy and machine learning, the secondment host (Rice, USA) in lensless imaging and the industrial partner (ZEISS, Germany) in spectroscopy and market analysis. The project allows PR to acquire expertise in silicon photonics technology's design, fabrication, characterization, and commercialization while giving back his expertise in metasurface design. The developed NIR spectrometers will find direct potential applications in wearable health monitoring systems, food screening, agriculture, and environmental screening that a remarkable global market size. The distribution of the work packages with distinct and clearly defined milestones and deliverables makes sure that the progress of the project will be monitored and matched with the work plan.

This proposal is primarily interested in algebraic geometry, a field that underpins geometric intuition with the precision brought about by calculation from algebra. The algebraic information of an algebraic variety - the set of common zeros of polynomial equations – is packaged in sheaves and organized in categories, which makes it possible to study these objects by importing the tools of homological and (non-)commutative algebra. This categorical approach is natural for many of the current leading questions in mirror symmetry, birational geometry, representation theory, and theoretical physics because it serves as a bridge between the geometric and algebraic language. It is also fundamental, as many properties and even classification results are not possible without it. The proposal is deeply interdisciplinary, and it connects broad areas of algebra and geometry. It naturally splits into three parts. The first aims to investigate one of the most fundamental properties of curves, namely contractibility, with non-commutative deformation theory. It will generalize classical results using modern language, at the same time producing many new explicit examples of rational curves in threefolds. Linking contractibility and non-commutative algebra will bring deep consequences for the birational and enumerative geometry of Calabi-Yau varieties, advancing areas of string theory. The second part studies surfaces with mild positive curvature (Fano, but with ineffective anticanonical bundle). The main objective is to prove a mirror theorem, packaging physical information with tools of homological algebra. The new heuristics, definitions, and techniques will open up an avenue to investigate higher dimensional settings. The third part involves reconstructing varieties from associated categorical data. I will tackle some hard open cases, developing new tools and combining them with classical methods.

The SiCyMBSIA (Silicon Cycle in the Mediterranean and Black Seas: An isotopic approach) project will be carried out by Dr. Diksha Sharma, an experienced researcher at the Centre National de la Recherche Scientifique (CNRS) in France under the supervision of Prof. Damien Cardinal. This project aims to unravel the intricate biogeochemical silicon (Si) cycling in the Mediterranean Sea (MS) and the Black Sea (BS). These two distinct marine environments offer unique opportunities for scientific exploration. The MS, with its unique oceanic characteristics, diverse ecosystems, and trophic regimes, provides an excellent opportunity for climate change research. Diatoms, an important phytoplankton group, play a crucial role in primary production and carbon export in this region. However, our understanding of their Si sources and limitations remains incomplete. By employing stable silicon isotopes (δ30Si) to analyze dissolved silicic acid and biogenic silica in the deep biogenic silica maxima and deep chlorophyll-a maxima layers, this project will quantify the role of diatoms and Si as nutrients and investigate processes governing dissolved silicic acid concentrations and biogenic silica dissolution in the intermediate and deeper layers of the MS. Along with this, understanding the seasonal pattern of exported biogenic silica from sediment traps will also be a novel aspect of this project. In contrast, the BS, characterized by its anoxic conditions and complex stratification, presents a unique challenge. This project will delve into the Si uptake by diatoms, sub-surface remineralization, and biogenic silica release through δ30Si analyses, shedding light on nutrient-driven diatom growth and biogenic silica production through hypoxic, anoxic, and H2S rich deep environments of the BS. Ultimately, this project promises to make a significant contribution to the international GEOTRACES programme and enhance our comprehension of Si cycling in these critical marine ecosystems.

HPV-FASTER-Implement aims to improve cervical cancer (CC) prevention. Although human papillomavirus (HPV) vaccination and CC screening programmes have significantly reduced mortality, they have reached a plateau because they remain largely inaccessible and underused by vulnerable populations, creating inequalities in the European healthcare system. This adds to the difficulties already faced by vulnerable populations in their efforts to maintain their mental and physical health. HPV-FASTER-Implement will create a Europe-wide knowledge framework on vulnerabilities and the health challenges they pose, as well as the tools to monitor their evolution. HPV-FASTER-Implement will work with stakeholder representatives, primarily from vulnerable populations, to identify context-specific strategies to deliver combined HPV vaccines and HPV-based CC screening to eligible vulnerable populations, thereby reducing the burden of CC in Europe. HPV-FASTER-Implement will develop health education interventions, communication activities and other services to meet the need of vulnerable population with high risk of CC and inadequate access to health services. Through stakeholder engagement, health literacy promotion, mathematical modelling, implementation research, and vulnerability mapping, we will collect, analyse and share knowledge on gaps and opportunities to improve CC prevention in Europe, and progress FASTER towards CC elimination. We will work to ensure that the data we produce are translated into policy recommendations aimed at strengthening national prevention programmes with interventions tailored to vulnerable populations. In this way, we can leverage limited resources to rapidly reduce CC mortality. We aim to reduce health inequalities by offering an innovative prevention intervention to women at risk, with the hope that 50% of those offered the intervention will take it. HPV-FASTER-Implement will make the necessary improvements to European CC prevention policies.

Over the past 5 years, antibody drug conjugates (ADCs) have shown impressive improvements in survival outcomes of solid tumors and hematological malignancies. With 14 ADCs already approved across different countries and more than 140 that entered the clinical development, they are intended to replace standard chemotherapies across multiple tumor types over the next decade. Although ADCs show great clinical efficacy, resistance eventually occurs, and it becomes critical to understand resistance mechanisms to guide the choice of the following lines of therapy for patients who progress on a given ADC. Given the complex nature of ADCs, immunocompromised mouse models (nude mice, NOD-SCID or NOG mice) and currently used clinical assays (standard radiology, IHC, WES etc) are not the optimal preclinical and clinical tools, to identify the multiple causes of resistance. The OASIS project aims to generate a biobank of different patient-derived organoids (PDOs), which better recapitulate ADCs resistance and integrate different assays, spanning from whole-body molecular imaging (Ab-radiolabeled PET scan or immunoPET), circulating tumor cells (CTC), plasma proteomics, to multiplex immunofluorescence (MIF) and machine-learning enhanced digital pathology (AI-digital pathology) to capture most of the parallel mechanisms of resistance to ADCs. Such tools will enable to define biomarkers of ADC resistance that can inform further therapeutic decisions.

Worldwide, ~7 million women live with or beyond Breast Cancer (BC), as 10-year survival rates exceeding 80% for early-stage (I-III) BC. Premenopausal BC accounts for 25% in the EU and 55% in low/middle income countries. Most premenopausal women with BC have high risk of recurrence, therefore standard treatment includes adjuvant chemo- (CT) and endocrine therapy (ET). However, treatment has substantial physical, emotional and social burden, which is often more pressing for younger compared to older patients. Gene-expression assays are used for post-menopausal patients to identify women who can safely forego CT without detriment on clinical outcomes, preserving Quality of Life (QOL). However, a definitive study has yet to be conducted among premenopausal women with high-risk HR+HER2-BC. The primary objective of PATH-FOR-YOUNG is to conduct a pragmatic randomized controlled trial (RCT) with 5000 patients validating the use of a gene-expression assay to drive adjuvant treatment decisions in this target population. PATH-FOR-YOUNG aims to achieve its objective in 7 years. The project (i) builds on and complements an ongoing twin RCT to ensure timely recruitment, (ii) leverages on a large international consortium of oncologists, pathologists, patient representatives, psychologists, sociologists, ethics and communication experts, biostatisticians, health economists, and technology providers, to assure complementary and multidisciplinary expertise, and (iii) highlights patient-engagement, participatory care, and early involvement of end users. PATH-FOR-YOUNG will also study implementation of digital self-management to support patients throughout the cancer journey and particularly while on ET to improve QOL and medication adherence. A full HTA will ensure a path towards cross-country implementation. PATH-FOR-YOUNG has the ambition to improve BC care, fully integrating the predictive, personalized, preventive, and participatory principles of health management.

Chronic pain is a major societal and economic European burden, affects one in five adults, and its inadequate relief indicates a major unmet need for effective and mechanism-based non-pharmacological treatments. In FRESCO4NoPain, we propose that maladaptive brain oscillatory activity is associated with persistent pain, and that non-invasive brain neuromodulation may provide a novel treatment strategy. For this, mechanistic insight is needed. We see this as the perfect opportunity to unite world-leading experts in pain neuroscience to train 17 uniquely skilled Doctoral Candidates (DCs) who will become the future generation of pain scientists, fully equipped to address unmet challenges within chronic pain. The DCs will be integrated in a one-of-a-kind network-wide training infrastructure conducting frontline research on non-invasive brain stimulation that targets persistent pain based on i) preclinical studies of the relevant brain circuitries, ii) human studies of the involved mechanisms, and iii) clinical studies. Through FRESCO4NoPain, DCs will access a unique set of basic, experimental, and clinical disciplines in both academic and non-academic settings, tied together by synergistic collaborations across the network. An application-based and patient-oriented mindset will permeate the consortium via the active involvement of cutting-edge MedTech companies, knowledge actors and end-users. Only such a truly interdisciplinary and intersectoral approach can provide the necessary ecosystem to go beyond the state-of-the-art, promote disruptive thinking while developing new methods that overcome current technological barriers in the complex field of interdisciplinary pain neuroscience. FRESCO4NoPain will deliver on urgently needed non-pharmacological therapeutic concepts for chronic pain and build on fundamental scientific insights regarding the role of neuronal oscillations in the brain processing of pain, thereby potentially helping millions of people with chronic pain.

The EFFecT Doctoral Training (DN) Network responds to the evolving landscape of RNA-based therapeutics and in particular antisense oligonucleotides (ASO). Over the last 25 years, only 21 antisense nucleic acid-based molecules have been approved by the FDA or/and EMA. However, the field is now at the tipping point of maturity to achieve regular translation from bench to bed side, provided that certain obstacles are successfully addressed. Our consortium involves experts from academia, industry, and non-profit organizations across nine European countries with first-hand experience in the successful translation of this new technology and in-depth knowledge of the remaining hurdles for its success. With leading scientists at different career stages, EFFecT’s core is form by nine academic and three industrial partners. EFFecT's objectives include addressing tissue-specific delivery challenges, imparting knowledge on diverse ASO modalities, and creating a roadmap for ASO therapeutics in Europe. The network's composition leverages over 20 years of experience in nucleic acid drug development, and was born from the successful COST Action "Delivery of Antisense RNA ThERapeutics" (DARTER). The EFFecT training network ensures a comprehensive education for Doctoral Candidates through knowledge exchange, secondments, research workshops and dissemination. This network is expanded with the collaborations of experts in communication, intellectual property, and open science that will train the DCs in good scientific practices. By addressing training gaps and fostering collaborations, EFFecT is poised to deliver the next generation of experts in this up-and coming field, elevating Europe's visibility and competitiveness in antisense RNA therapeutics.

Effective (organic) waste management and renewable energy supply are essential in our present society, such as meeting targets of the European Green Deal and the Renewable Energy Directive. Anaerobic digestion can tackle both challenges simultaneously, and has been commonly applied for renewable energy recovery in the form of biogas from organic waste. The complex and sensitive microbial interactions to environmental stressors can cause the failure of anaerobic digestion, imposing challenges for innovation. In LeAD, we introduce the microbial niche nexus concept (tuning microbial communities and their metabolic pathways to achieve multidimensional microbial networks) to achieve more resistant/resilient anaerobic digestion systems, thus improving resource recovery from waste sources under stressed conditions. Hence, LeAD aims to train the next generation environmental biotechnologists in order to address key knowledge gaps and develop models and technologies in anaerobic digestion responding to stressed environmental conditions, which will revolutionize resource recovery from waste towards circular bioeconomy and sustainable development. The 14 tailored projects are tailored based on the design-build-test-learn cycle to train the doctoral candidates with systems knowledge to deal with challenges for transiting waste removal towards resource recovery through anaerobic digestion. To train the 14 doctoral candidates via an international, intersectoral, and interdisciplinary program, LeAD brings together experts from several disciplines, forming a consortium of eight beneficiaries and five associated partners (including three industries). Through both local and network-wide activities and events, LeAD will educate next-generation talents with competitive transversal skills and capacities both to the academic and non-academic sectors, further profoundly influencing the future bio-economy and society.

Cancer immunotherapies have been established in a growing number of clinical indications and the pace of development is massively accelerating. Currently over 6.000 clinical trials are investigating immune-related treatments in oncology especially in combinations. It includes both adoptive cellular therapies and immune modulating treatments like immune check point blockade. In contrast, the understanding of how such therapies mediate their mode of action is still mostly poorly understood. In particular, the role of distribution and relocation of immune cells after therapeutic interventions remains unknown. This is surprising, as immune cell interactions are a hallmark of therapeutic immune responses. T-RAFIC will enhance understanding of immune cell trafficking under therapeutic influence. It will open new paths and avenues to treatments, boost their efficacy and help prioritizing the plethora of immune therapeutic combinations. In the past, detailed analysis of cellular distributions was facing technical barriers. Advances in technologies, now permit tracking and visualization of cells in vitro and in vivo at an unprecedented resolution, allowing for the first time studies on immune cells under therapeutic influence. This emerging field of research has enormous potential and key importance for next generation of researchers in oncology and beyond. However, experts in this field are missing and this threats European research, development and medicine. Therefore, T-RAFIC joins forces of 19 academic and three industrial partners from nine European countries to conduct an innovative and interdisciplinary approach combining cell imaging with bioinformatics, cell engineering and clinician expertise. The network bundles recognised expertise in cancer immunotherapies, empowering European research and innovation and ensuring a sustainable cooperation in science and training.

The European Union has been challenged to contribute to the global aim of providing sustainable solutions to the current and future needs on synthetic compounds and materials in the coming years. In this sense, the development of sustainable chemical processes is one of the most important features in modern chemistry. It has become a key research area worldwide, providing solutions to important societal demands by optimizing the use of natural resources and minimizing waste and environmental impact. Among the relevant methods for achieving this goal, catalysis represents a key and central approach. Both Organocatalysis and Metal Catalysis have emerged as solutions to the problems in this context. Despite the enormous advances made towards both types of catalysis, the development of more efficient and general catalysts, as well as synthetic methods is still a challenge. A very similar research-road has occurred in the Photocatalysis area, using visible-light as mild and sustainable energy source. In this context, the pharmaceutical industry has a great impact in our society. Well-stablished organo- and, especially, metal-catalysis have been largely implemented in the chemical industry, both on a micro and ton scale. However, there are only few timid academic applications of novel photocatalytic visible light methodologies into industrial goals. Therefore, the development of cheaper and straightforward methodologies to the incorporation of key photochemical processes is an important field and has a tremendous impact in the industry field. Therefore, greater blending of academia and industry would be desirable for the implementation of photocatalysis in the chemical industry world. Students who can access this doctoral network will have the opportunity to work in European Funded academic researchers and in three Big Pharma companies in a hot field such as photocatalysis with the aim to develop new real industrial solutions.

Future networks will support several applications that require extending fiber-optic quality of experience to wireless links. This means connectivity at extremely high data rates with deterministic performance (guaranteed requirements in terms of reliability and time response). Virtual avatar presence, traffic control, autonomous driving, remote health monitoring, cyber physical systems for intelligent transportation, industrial automation are only a few examples of anticipated use cases. Owing to the large amount of available bandwidth, the European Telecommunications Standards Institute has identified terahertz (THz) as a key technology for future wireless networks. TeraWireless is the first EU training-through-research industrial doctoral network of doctoral candidates and senior supervisors fully committed to lay the theoretical, algorithmic, and architectural foundations for enabling THz systems at optical speed with deterministic performance. TeraWireless will 1) put forth the innovative ultra-MIMO (multiple-input multiple-output) technology for increasing the data rate and link reliability through spatial multiplexing and superdirective beamforming, and will pioneer the development of electromagnetic and communication models for evaluating its performance in low-scattering THz channels, where multipath propagation cannot be exploited, by integrating sensing, localization, communication capabilities; 2) leverage the emerging concept of semantic and goal-oriented communications by folding message semantics and goals of communication within communication layers; 3) develop innovative physics-based ML solutions for energy-efficient, robust, reliable, and explainable-by-design implementations; 4) make available to the research community the EU’s and world’s first open-access and open-source simulation environment - integrating ray tracing, link-level, and system-level features - for evaluating and optimizing THz large-scale deterministic networks at optical speed.

In the context of climate change, Europe is facing new challenges that are threatening food security. There is thus an urgent need for the development of innovative strategies to improve plant tolerance to stress. Notably, recent years have already shown an unusual frequency of heat waves during the summer, a stress condition particularly threatening for yield as it cannot be mitigated in the field. Like many other kinds of stress, heat stress has a detrimental effect on growth due to reduction of the cell division activity in meristems. There is accumulating evidence that this growth reduction depends at least partly on the activation of the plant DNA Damage Response (DDR). The HeatDDR proposal aims at building on the acquired knowledge to decipher the links between the DDR and plant heat stress responses, and to fine-tune these cellular responses in order to allow plant survival without impairing growth. By bringing together groups with complementary expertise and private companies interested in this topic, HeatDDR will combine multiscale approaches including biochemistry, molecular biology, cell biology, genetics, computational biology and plant phenotyping to tackle this question and to train a new generation of scientists specializing in this emerging field. Trainees will work on both Arabidopsis and crops and will thus be aware of different plant models, and on specific challenges associated with breeding. Through the HeatDDR programme, ESRs will receive hands-on training on advanced laboratory techniques and develop transferable skills, thereby ensuring their successful integration on the job market either in the academic or in the non-academic sector, and setting the ground for the construction of European network of collaboration in this field.

New technologies of compact accelerators, in particular plasma accelerators, and laser-based x-ray sources, are on the verge of reaching maturity in this decade, making today the perfect time to steer them towards a broader scope of applications in academia, medicine and the industry. Training the next generation of entrepreneur-minded early-stage researchers on such a disruptive technology will enable them to start successful careers with significant societal impact. This is the goal we pursue with the Marie Skłodowska Curie Action Doctoral Network EPACE (European compact accelerators, their applications, and entrepreneurship). EPACE fosters a culture of excellence, innovation and critical thinking to help the next generation explore opportunities and guide it towards significant contributions in line with the EU missions. Emphasis is put on applications in industry (muon tomography), medicine (FLASH effect with particle beams from plasma accelerators), and impactful progress (reduced energy consumption of particle accelerators). An extensive curriculum from a world-class European business school will help the students identify and transfer the most promising innovations into commercial products. Coordinated by DESY, EPACE gathers 31 industrial and academic partners in Europe, to provide 15 PhD students with great scientific expertise, a thorough awareness of EU values and a drive towards entrepreneurship.

The future economic growth in Europe requires engineers and researchers capable to design, develop and implement new information technologies to support explosive data-driven transformation of economy, public and government activities. The analysis of this data demands a massive increase in processing power and communication bandwidth. Current information, computing and processing technologies strongly rely on the classical digital approaches and architectures developed by von Neumann. However, technological progress rates of digital technologies are flattening out and are about to hit their ultimate, physical ceilings (“end of Moore’s law”). This growing gap between what is demanded and what can be delivered becomes exacerbated by the increasingly inacceptable energy consumption of the global ICT infrastructure, whose relevance is amplified by the pressing and approaching climate crisis. In this situation, both academic and industrial ICT research has started to investigate and invest in so-called “unconventional”, nature-inspired approaches to computing which radically depart from the classical digital paradigm. European Doctoral Network on POSTDIGITAL Plus brings together internationally leading teams from academia, research centres and leaders of industry, including IBM, Thales, Hewlett Packard Enterprise Belgium and three regarded start-ups NcodiN, Akhetronics and VLC Photonics in the field of optical computing to train a cohort of 15 doctoral candidates in the inter-disciplinary fields of emerging disruptive neuromorphic computational technologies and their applications. POST-DIGITAL Plus has the ambition and the vision to create a new generation of scientific and industrial leaders that will greatly contribute to strengthening Europe’s human resources and industry competitiveness in future digital and post digital economy and technology.

The future energy mix will include a variety of fuels. E-fuels allow to store the excess renewable energy into high energy-density chemical compounds representing the ideal candidates for energy transition in Energy Intensive Industries (EIIs). The DESIRE network will train the next generation of specialists in exploring the use of e-fuels, in existing combustion devices, to better guide the energy transition and to help the decarbonization of EIIs in Europe. The academic and industrial partners of DESIRE will work synergistically to generate a cohort of 15 well-trained young scientists with inter-disciplinary skills in combustion science, mechanical and chemical engineering, computer science and modelling that will be ready to propel and advance future engines towards pollution control, fuel-flexibility and higher efficiencies. Such a broad spectrum of training is currently lacking due to the fragmentation of the emerging field of sustainable combustion across Europe. Perhaps more importantly, the need, nature and magnitude of these new skills is only now emerging. The DESIRE network will equip its Doctoral Candidates with a unique combination of skills essential to become future research leaders or entrepreneurs in the sustainable energy sector. They will drive this research field forward and accelerate the energy transition. The main scientific goal of DESIRE is to develop predictive tools including mathematical-numerical models and experimental measurement techniques able to describe the combustion of e-fuels that can then assist engineers in designing new technologies and/or modifying/adapting existing combustion equipment and technologies to be suitable to use these powerful fuels. The program is heavily supported by key-companies in the transport sector (Rolls-Royce, Safran), fuel and chemicals production/ distribution (Air Liquide), and electrical/mechanical power technology (Condevo, ENGIE, MITIS).

NeuroNanotech will train eleven researchers to tackle one of the major challenges in Europe’s ageing population - neurological diseases. The ability to monitor and modulate neural activity using interfaces has enabled a better understanding of brain function and has led to therapeutic solutions for some neurological disorders. Yet, fundamental technological challenges, such as ensuring proper brain tissue interfacing and reliable long-term recording/stimulation after implantation, impede widespread clinical use. New approaches to provide effective treatments are urgently needed. NeuroNanotech will develop novel nanostructured flexible neural interfaces with highly improved tissue integration, minimizing foreign-body reactions and tissue scarring and allowing stable stimulation treatments. As main innovation, we will develop minimally invasive, ultra-sensitive spintronic magnetic sensors able to record stably without interfering with stimulation signals and avoiding electrode degradation. Connecting both interfaces, we will construct a low-invasive, closed-loop neurostimulation system that integrates feedback signals from the neural activity and provides real-time stimulation of the target structures according to the patient´s needs. To achieve these goals, NeuroNanotech brings together experts in nanotechnology, device engineering, neuroscience and clinical neurology. The individual research projects are highly interconnected, ensuring interdisciplinary training. Researchers will benefit from training in advanced research and relevant complementary skills, imparted by an international and intersectoral consortium of research institutes, universities, companies, hospitals and social organisations from 9 different countries. We will provide researchers a unique environment focused on innovation and collaboration, with a view to commercial applications of the research results. This framework will open researchers avenues in both academia and health-related industry.

LIGHTinPARIS is a MSCA COFUND Doctoral Programme in the field of Sciences of Light aiming at promoting interdisciplinary, international and intersectoral research projects at University Paris-Saclay (UPSaclay). The Sciences of Light cover a very broad field, from fundamental physics to technological applications in photonics, quantum mechanics and biomedicine and open up an increasing number of technological applications. Among these sciences, photonics is one of the key enabling technologies identified in the Horizon Europe strategic plan. The Paris-Saclay region has been hosting numerous prestigious research laboratories for several decades. To gather its strengths, UPSaclay has been created in 2020 by grouping several academic and research institutions located in Saclay area. It joins 8,100 researchers working in 275 laboratories. UPSaclay was ranked 15th in the 2023 Shanghai University ranking, and 3rd in physics (1st in Europe) in the Global Ranking of Academic Subjects. Regarding Sciences of Light, UPSaclay gathers 700 researchers working in 28 laboratories across 5 graduate schools. UPSaclay graduates every year 150 engineers and 70 PhDs specialized in optics. In addition, UPSaclay hosts many world class research facilities. The Institute for the Sciences of Light (ISL) has been created in 2020 to foster interdisciplinary synergies among the graduate schools of physics, chemistry, engineering, geosciences and life sciences and promote international and intersectoral relations. The LIGHTinPARIS programme through ISL will recruit 30 PhD fellows (2 cohorts of 36 months each). Industrial and international secondments will also be implemented to allow PhD fellows to shape their careers by acquiring technical skills and networking relationships. Numerous trainings will also be offered to ensure that doctoral students have both technical skills and soft skills by the end of their PhD.

Located in Ljubljana, Slovenia, the Jožef Stefan Institute is the national leader in quantum research. Supported by the Marie Skłodowska-Curie Actions programme, the SQUASH project – Slovenian Quantum Science Hub – will employ 40 foreign postdoctoral researchers. The fellowships are designed to advance their research skills in four multidisciplinary fields: quantum theory, quantum materials, quantum technology, and quantum computing & information. With a broad range of international and intersectoral secondments, as well as career-developing training programs, fellows will gain a blend of additional versatile skills, significantly boosting their career-growth opportunities. The project aims at developing skilled and innovative quantum workforce across research, technology, and academia to tackle the upcoming challenges of the second quantum revolution.

SEANERGYS creates an integrated European software solution that optimises the operation of supercomputers. In doing so, it addresses four different objectives: reducing the amount of energy used for real-world workload mixes as the primary objective, optimising resource utilisation, enhancing system throughput and reducing response time as secondary objectives. Since these objectives can conflict with each other, site-specific policies define the weights attached to each, and the SEANERGYS SW suite will tailor system operation towards the combined optimum. Possible scenarios include improving the throughput of HPC systems, generating more R&D results for a given energy budget, or produce a fixed set of R&D results with less energy, while striving to keep response times constant. The solution consists of a comprehensive monitoring infrastructure (CMI), an Artificial Intelligence data analytics system (AIDAS), and a dynamic scheduling and resource management system (DSRM). The CMI gathers data from hardware and software sensors, and correlates it with scheduler information to identify jobs that do not fully utilize allocated resources. Users receive automatic feedback on energy and resource use for each run, plus information on how to optimize these. The DAIS leverages AI models trained with a vast set of operational data of the participating HPC sites. It fingerprints resource usage patterns, predicts future job behaviour, and identifies complementary job profiles for potential co-scheduling. Finally, the DSRM utilizes these insights to develop scheduling policies that maximize resource utilization and energy efficiency, and supports jobs/applications with dynamic and adaptable resource profiles. The SEANERGYS solution will be ready for deployment up to Exascale level. To ensure production-quality, the project builds on results from European projects, the competency of well-established research groups and companies, and widely used open-source codes. These are input for an integrated software system that achieves the functionality, performance and stability needed by European HPC centres, defined by KPIs and acceptance criteria and processes established at the project start. An agile, professional software development method will leverage a modern DevOps framework and strive to provide end-to-end traceability by linking and tracking requirements, interface, functional and performance specifications, code design and development steps, and validation/verification throughout the development lifecycle. Validation/verification measures will include code reviews, automated SW quality analysis, unit and integration tests and a verification suite. The project will implement a staged testing and validation process, with functionality tests on single-nodes, scaling tests on mid-sized platforms, and finally acceptance tests on production supercomputers.

EUAqua.Org is aimed at boosting organic fish production in Europe by developing highly innovative solutions to fill key knowledge gaps and overcome the most relevant factors limiting the competitiveness for organic farming of Atlantic salmon, European sea bass, gilthead sea bream, and rainbow trout. Key technological advancements in phenotyping, genotyping, and genomic prediction methods will be developed by EUAqua.Org through the integration of different disciplines and approaches. This will provide essential tools for cost-effective, welfare- and environment-friendly organic aquaculture. The implementation of these tools at the industry level will be ensured by a comprehensive scientific, public, and industrial communication and dissemination programme, with exploitation of the project objectives and key results to create impact, including a multi-module open-access online training course that will be co-developed with key stakeholders (breeding companies, fish farmers, feed producers). In parallel, a tailored set of intervention strategies will be designed to promote awareness and acceptance of OA products in European consumers, through a behavioural economics approach. The project will build upon outputs of completed and ongoing national and EU projects, fully exploiting existing knowledge and leveraging the direct involvement of EUAqua.Org partners in multi-disciplinary research on advanced fish genomics, fish nutrition, fish health and welfare, consumer studies.

BUTTERFLY aims to significantly enhance society’s capacity to appraise, foresee, and respond to the threats posed by cascading impacts of pollinator decline. To reach that goal it will establish a test system of geographically well spread multi-actor communities across sectors for co-creating proactive pollinator restoration solutions and: (1) collect, integrate, manage and share ecological and spatial information on a wide range of known and lesser known pollinators and pollination services provided for wild and cultivated plants, across Europe and selected overseas territories; (2) advance the monetary and non-monetary valuation of marketed and not marketed direct and indirect ecosystem functions and services provided by pollinators, and advance ecosystem accounting; (3) comprehensively model and quantify the macro-economic implications of pollinator decline and country-specific economic butterfly effects of dependencies on pollinators, and assess policy options and scenarios; (4) assess how five key biomass supply chains (food/micronutrients, pharmaceuticals, cosmetics, biomaterials, biomass energy) depend on pollination and co-create pollinator restoration options that increase resilience of these supply chains; (5) devise, co-create, test and implement transferable tools, interactive atlases and guidelines that enable systematic mainstreaming of proactive pollinator stewardship in vulnerable sectors; (6) conceive indicators for human dimensions and assess and exploit the socio-cultural capacity of the concepts: ‘pollinator stewardship’, ‘eco-literacy’, ‘historical agency’ and ‘slow hope’ in reversing pollinator decline. It will inform EU policy processes and build strategic alliances for high-level impact. The BUTTERFLY network of Living Labs will accelerate knowledge transfer and uptake of new business models and serve as breeding place for multi-actor co-creation of knowledge and sustainable solutions, paving the way to pollinator stewardship in all sectors.

The Cir4Fun Project endeavours to transform the furniture industry by championing circular economy principles across the product life cycle. Through innovative strategies, DPP and digital solutions supporting mechanisms, it aims to enhance furniture sustainability, eco-labelling, and consumer engagement while aligning with relevant regulations and initiatives. Cir4Fun's approach involves creating a comprehensive circular economy roadmap, defining content for a Furniture DPP, developing circular business models and eco-design guidelines, and establishing new assessment methodologies for maintenance, reparability, refurbishment, remanufacturing and recyclability. All this knowledge will be integrated in a holistic Furniture Assessment System (FAS) including a Sustainable Index System, d-LCA, LCC, SLCA. FAS will support the furniture eco-scoring system and DPP. Additionally, it focuses on interoperability, data sharing and data management with reliable approaches to enable simulation testing to inform supply chain strategies and extend product lifespan. Social engagement with stakeholders is emphasized to promote sustainable behaviours and circular practices, ultimately supporting new regulations and standardization in the furniture industry. The project outcomes will be implemented and validated in 3 use cases addressing different value chains across Europe and the findings will be widely circulated across the furniture ecosystem in Europe.

PROTEIN4IMPACT aims at evaluating the nutritional, health, safety and quality aspects together with the environmental and socio-economic impacts of protein novel foods (NFs) obtained from unconventional sources. In order to close the project loop by maximizing the positive impact on the transition towards healthier, protein NFs, the overall approach to alternative protein production in PROTEIN4IMPACT is based on utilization of selected agri-food and fisheries & acquaculture by-products as primary feedstock as well as on the utilization of natural protein producers, i.e. fungi, bacteria, insects micro- and macroalgae. The secondary by-products formed along the value chain will be up-cycled for their use in the food production cycle or for the production of process energy. The obtained proteins will undergo modification and functionalization followed by a sensory evaluation and testing in food human trials and in aquaculture as feed ingredients. The project will also test the feasibility of producing NF products by simulating realistic industrial scale, using different methods and tools such as LCA, LCC, RA, and TEA as well as Digital Twins and real time AI-driven monitoring and DSS tools. The optimization of parameters affecting the protein NF production will be evaluated at the end to increase protein content and the impact assessment evaluated on each single stage (extraction, characterization, modification/functionalization of protein rich fraction, production of NFs) and on the integrated processes. PROTEIN4IMPACT NF acceptance and social relevance –also through sensory evaluation actions- will be assessed in four markets (Europe, USA, Africa and Asia) to benchmark the European scenario with the rest of the world. Only by using an integrated approach like the one proposed in PROTEIN4IMPACT will it be possible to evaluate the correct feasibility in the use of alternative proteins in the food sector with a realistic sustainable approach.

New emerging applications demand performance requirements that exceed the capabilities of 5G networks, requiring a rapid evolution towards 6G networks. 6G is expected to offer data rates of the order of Tbps, time responses of the order of sub-milliseconds, and localization accuracies of the order of sub-centimeter, while meeting united nations’ sustainable development goals. This calls for the deployment of paradigm shifting technologies and design methods, and the use of new frequency bands, including the deployment of reconfigurable metamaterial transceivers, the integration of communication and sensing functionalities, and the migration towards the sub-terahertz spectrum. This will make 6G an extremely complex system to model and optimize. Digital twins (DTs) and machine learning (ML) are two vital technologies to tackle the modeling and optimization complexity of 6G. A DT is a virtual replica of the 6G physical network. DTs are essential to model complex systems in real time, providing valuable insights into their behavior and performance, as well as for generating enormous amounts of training data. ML provides advanced analytics and decision-making capabilities, enabling 6G communication systems to self-optimize, self-configure, and self-heal. The integration of DTs and ML offers a powerful approach for modeling, simulating, and optimizing 6G communication networks. It is expected to lead to the creation of a highly intelligent and dynamic network environment, where physical and virtual objects interact seamlessly, and where decisions are made and executed in real time. TWIN6G is the first-of-its-kind staff exchange research and transfer-of-knowledge program whose aim is to build the world’s first open-access and open-source digital twin emulator to design 6G networks, integrating accurate physical models for emerging technologies and physics-based ML designs for dynamic and real-time network optimization.

The project “The Activist, the Archivist, and the Researcher: Novel Collaborative Strategies of Transnational Research, Archiving and Exhibiting Social and Political Dissent in Europe (19th-21st centuries)” (ACTIVATE) fosters inter-sectorial and interdisciplinary collaboration through the international research cooperation of 16 academic and non-academic institutions from 7 countries across Western, Central and Eastern Europe. ACTIVATE’s objective is to develop innovative methodologies and new knowledge as well as share best practice based on the principles of diversity, inclusiveness and open science between researchers, archivists, curators and public educators through a reflective approach on social and political dissent in a long-term and comparative perspective. By focusing on the transnational circulation of people, ideas, discourse, practice and archives, ACTIVATE aims first to contribute to a new narrative on European protest and its relations with non-European spaces. Secondly, the project engages reflective archival, research and exhibiting practices to explore the role and impact of archives on different space and time scales, approaching them as an ecosystem of active agents of memory and change. Through secondments and networking, ACTIVATE partners will share their expertise and best practice on material, audiovisual and born-digital documents and data. They will organise thematic seminars, workshops, training and public programmes to increase institutional outreach that will serve as a model for future endeavours, ensuring cooperative relationships and impact on the wider community beyond the life of the project. ACTIVATE strives for new synergies between academic research and heritage institutions, fostering better knowledge, integration and promotion of dispersed cultural heritage, which European democracies need to preserve with care.

The main objective of GreenEO is to provide improved satellite-based environmental information to support sustainable nature protection practices across four competing land-use areas: cities, agricultural areas, forests, and ecosystems. Through combined exploitation of new Earth Observation products, digital infrastructure, and atmospheric and land surface models using machine learning and data assimilation, GreenEO will provide environmental information and stakeholder engagement practices to support the implementation of the Zero Pollution (ZP) and Biodiversity aspects of the European Green Deal (EGD). The project will serve as a proof-of-concept to enhance specific services provided by Copernicus and EUMETSAT in support of the EGD implementation. GreenEO aims to support the transition towards more sustainable land use practices in Europe and proposes a transformative governance system, relying on a data value chain enhanced with active stakeholder engagement and co-creation. The value chain proposes the uptake of satellite data, integrated in a modelling development chain and followed by value creation modelling applications. In cities, GreenEO will develop three satellite-based approaches of high-resolution urban-scale air quality maps to engage relevant stakeholders to support the ZP strategies. For agriculture, GreenEO will address impacts on nitrogen emissions, deposition, and biodiversity. It will create satellite-based high-resolution emission inventories, deposition, critical load exceedance maps, and identify areas with high recovery potential. GreenEO will develop a forest fire service that will revolutionize the monitoring of wildfires over Europe. GreenEO will create novel ecosystem monitoring indicators such as city greening indicators, ecosystem area and condition indicators. GreenEO will advance seamless climate-weather and environmental services in Europe, by proactive links to EUMETSAT, WMO, the Copernicus Services, EEA and EU Missions.

JENNIFER3 aims to continue, further develop and finalize the research and communication activities started in 2015 within the JENNIFER project and currently being carried on by the JENNIFER2 MSCA-RISE project, which will conclude in may 2025. The community forming the JENNIFER3 consortium is putting together three research programs at experimental facilities located in Japan where very rare processes can be observed: accelerator produced neutrinos (T2K and HyperK collaborations), cosmic neutrinos detection (HyperK collaboration) and a high luminosity electron-positron collider (Belle II experiment at SUPERKEKB). Such programs use different approaches, are sensitive to different “messengers” of the new physics world and are essential to complement the so called “energy frontier” investigation which is carried on at the LHC. Sinergy and knowledge sharing among them is the drive force of the JENNIFER3 project, which on one hand fosters the collaboration of European scientists with the Japanese research community, while on the other hand promotes close collaboration among different European research groups around key technologies, such as cloud computing and data network developments, machine learning applications for data filtering and reconstruction, photon detection, solid state detectors, particle beam monitors. Collaboration with private sector technology providers is also essential to reach the scientific objectives of the project. All project members are also committed to disseminate and communicate their work to the scientific community and to the European society through various initiatives aiming to different targets. Cross fertilization between different research communities and approaches is the real added value to boost the project impact, both in terms of scientific results and of researchers’ careers.

We propose a conceptual design study for a 12-metre wide-field spectroscopic survey telescope (WST) with simultaneous operation of a large field-of-view (3 sq. degree), high-multiplex (20,000) multi-object spectrograph (MOS) and a giant 3x3 arcmin integral field spectrograph (IFS). In scientific capability these specifications place WST far ahead of existing and planned facilities. In only 5 years of operation, the MOS would target 250 million galaxies and 25 million stars at low spectral resolution plus 2 million stars at high resolution. Without need for pre-imaged targets, the IFS would deliver 4 billion spectra offering many serendipitous discoveries. Given the current investment in deep imaging surveys and noting the diagnostic power of spectroscopy, WST will fill a crucial gap in astronomical capability and work in synergy with future ground and space-based facilities. We show how it can address outstanding scientific questions in the areas of cosmology; galaxy assembly, evolution, and enrichment, including our own Milky Way; the origin of stars and planets; and time domain and multi-messenger astrophysics. WST’s uniquely rich dataset may yield unforeseen discoveries in many of these areas. The study will deliver telescope and instrument designs, cost estimates, an updated science white paper and survey plan, concept studies for data management, and a facility operation concept. The telescope and instruments will be designed as an integrated system and will mostly use existing technology, with the aim to minimise the carbon footprint and environmental impact. We will propose WST as the next ESO project after completion of the 39-metre ELT. Our consortium includes institutes from Australia, which has a strategic partnership with ESO and aims to apply shortly for full membership. Together with ESO and institutes in 9 European countries, our team has the necessary technical and scientific expertise, and brings 70 years of in-kind effort to the proposed study.

The IM4CA proposal unites leading European methane experts in a concerted effort to establish the scientific fundament needed to bring the climate forcing of methane under control. Specific objectives are to: 1) Strengthen methane mitigation policy world-wide with actionable information on local methane emissions and key driving processes, 2) Provide the EU with the measurement and modeling capacity needed to monitor its methane emissions and assess its progress towards the 30% emission reduction target of the European methane strategy and the global methane pledge, 3) Explore and understand climate feedbacks on natural methane sources and sinks, and 4) Improve the accuracy of climate scenarios by resolving the controversy about the causes for the recent growth rate variations in global methane. To achieve these objectives we address a selection of key uncertainties that have thus far limited the progress towards these goals by: i) building up critical new infrastructure for monitoring methane emissions in Europe and Tropical Africa, ii) developing methodology for efficient use of existing and upcoming satellites for measuring methane and the land surface properties needed for characterizing and attributing its emissions, and iii) translating the knowledge obtained into reliable projections of future methane and efficient emission mitigation scenarios. In doing so, the IM4CA project will enable a breakthrough in meeting the work program challenge of enhancing the quantification and understanding of natural and anthropogenic methane emissions and sinks. It will provide enhanced European assessment capacity of short- and long-term changes in methane sources and sinks integrating information from multi platforms and novel observations and transfer that capacity into actionable information needed to combat climate change.

The explosive growth of available information requires a disruptive shift in the development of high-bandwidth and energy-efficient communication technology. At the same time, space-communication is critical with the acceleration of human activities in space. Laser-based space-light communication is attracting great interest due to the increasing demand for inter-satellite and ground-to-satellite communication. However, as the light intensity diminishes over long-distance, the development of a new light-coding method is crucial for reliable high-speed information transmission. It is questionable if future bandwidth requirements for earth and space communications will be met by conventional lasers, while keeping the overall power consumption manageable. SpinDataCom will overcome these limitations and revolutionize space and earth communications combining the advances in spintronics and semiconductor lasers with injected unequal number of spin up/down electrons. The electron spin imbalance in spin-lasers is transferred to the circular polarization of light which enables ultrafast polarization modulation, low-power consumption and highly-efficient information coding, implemented even on a single photon. Our approach can be transferred to existing fiberoptic networks, exceeding conventional transmitters in data rates and power efficiency. Gathering experts from 4 EU countries, SpinDataCom will build a disruptive proof-of-concept (TRL4) for spin-lasers, enabling ultrafast modulation via full electrical spin and magnetization control, to enable groundbreaking technologies for space and Earth data communication. This ambitious approach has potentially transformative impacts on society, economy, and environment due to its many applications on Earth and for space. With our Industrial Advisory Board, a strong communication, dissemination and exploitation plan, global visibility on SpinDataCom’s results will be ensured while enabling the transfer towards commercialization.

The ability to evaluate EU's climate and sustainability targets is currently limited by challenges in monitoring ecosystem greenhouse gas (GHG) exchanges and other services in an accurate and timely manner. Important knowledge gaps concerning processes and drivers of GHG exchanges persist, that further hamper our predictive capabilities. The absence of coherent approaches to collect, interpret and integrate data on terrestrial GHG stocks and processes into predictive models limits the EU’s ability to monitor ecosystem services and thus to reach its climate ambitions, including the Paris Agreement of Climate Convention and European Green Deal. NextGenCarbon aims to develop a novel framework for advancing our understanding of the European GHG budget. To reach this goal, we will: 1) improve and enrich existing measurements on ecosystems; 2) assimilate these data into state-of-the-art modelling frameworks; 3) create seamless scenario prediction systems; and 4) provide guidance to policymakers on the magnitude, evolution of and future risks to GHG fluxes. Our exceptional multidisciplinary consortium links leading experts developing the next generation of ground and EO-driven observations, with several groups at the cutting edge of carbon cycle and land surface modelling, plus teams pushing the boundaries of data assimilation, complex system modelling, forest management and disturbance monitoring, land-use and GHG inventories, and communications. It also involves active engagement with diverse stakeholders, including landowners and managers, GHG exchange modelling community, international community related to environmental monitoring, climate policy support and GHG inventory experts, and policymakers. In doing so, NextGenCarbon will pave the way for high-accuracy and seamless estimates of national to continental and global GHG budgets from the recent past into the coming decades, making a vital contribution to EU's climate mitigation strategies.

The ELEQUANT project proposes a paradigm shift in quantum technology by exploiting flying qubits, presenting a transformative alternative to mainstream approaches such a superconducting or semiconducting qubits. While photon-based flying qubits face challenges in real-time manipulation and interaction due to their fast propagation speed and weak photon-photon interaction, ELEQUANT aims to harness the potential of electronic charges for superior scalability and connectivity. Through pioneering research in the manipulation of electronic wavepackets in semiconductor nanostructures, the project strives to achieve the ambitious goal of realizing high-fidelity flying charge qubits and demonstrating entanglement between them. Key objectives include the development of novel quantum materials platforms based on strained Ge and multi-layered graphene. By establishing a comprehensive roadmap for solid-state flying qubit technology, ELEQUANT seeks to accelerate innovation in quantum technology and foster collaborative partnerships with industry stakeholders on a European scale. With a focus on scalability, connectivity, and coherence, ELEQUANT aims to propel quantum technology into a new era of unprecedented capabilities and applications.

Half of the protein directed towards animal feeding is wasted due to incomplete protein digestibility, and the distinct amino acid profiles found in both plants and animals. This generates serious pollution problems for our soils, aquifers, and atmosphere (e.g. livestock contribute to 87% of total ammonia emissions in agriculture). Moreover, EU faces significant challenges in providing adequate protein sources for animal feed (97% of soybean meal is imported; €1.5 billion/year). Hence, it is imperative to identify a sustainable solution for animal protein supply. SYNFEED will demonstrate that by developing a new interdisciplinary technological approach, it is possible to generate proteins that can produce a radical paradigm change in the way animals are fed, highly reducing both the environmental impact and external dependence on raw materials of the EU. Using the broiler chicken as a model, SYNFEED will i) generate new precision nutrition knowledge (proportion of amino acids to fulfil the requirements and dynamics of protein hydrolysis in the targeted species); ii) design several candidate sequences using this nutritional information by protein engineering techniques (combining AI and molecular modelling); iii) generate these candidates in cell-free systems adapted to the final host and evaluate them in a new iterative procedure maximizing expression and digestibility potential; iv) optimize the sustainable biosynthesis of the selected protein with sustainable hydrogen-oxidizing bacteria strains; v) evaluate the effectiveness of the protein in broilers (productive performance, animal health and welfare and reduction of nitrogen losses), and the sustainability of SYNFEED solution with a life cycle assessment. This ground-breaking approach will replace conventional animal feeding, positioning the EU as a leader in biosynthetic protein generation, promoting the emergence of biotech companies and reducing livestock environmental impact.

From violinists to metal welders, finely tuned hand and arm movements are the foundation of craft, while all of us rely on proficient use of hands for the activities of daily life. Yet, more than 25 million people worldwide lost functional movements to subcortical stroke. Subcortical stroke often interrupts the communication between the cortex and the cervical spinal cord circuits, which leads to permanent hand and arm paralysis. The result is a vastly reduced quality of life and enormous socioeconomic burden for the affected, their families, and the society. A treatment that can effectively restore functional movements after subcortical stroke does not yet exist. Still, the motor cortex, which orchestrates movements, and the spinal cord motor circuits that directly control muscles remain largely intact. We aim to reverse the hand and arm paralysis of people with subcortical stroke by developing a digital bridge that reconnects the motor cortex with the cervical spinal motor circuits. This brain-spine interface consists of fully-implantable recording and stimulation systems that link cortical signals to spatiotemporal sequences of epidural electrical stimulation targeting spinal cord regions involved in the production of hand and arm movements. Our preliminary results in people with spinal cord injury strongly indicate that the brain-spine interface can restore natural control of movement and promote neurological recovery. Therefore, we are confident that a cervical brain-spine interface can reverse hand and arm paralysis incurred by stroke and, therefore, become the first viable treatment option for subcortical stroke survivors. Beyond the development and validation of the cervical brain-spine interface for stroke survivors, this project will build the intellectual property necessary to secure funding that will bring this treatment into widespread clinical use.

Innovation in the genomics field is extremely intense and requires high up-front investments. The toolbox of sequencing platforms with unique features that require specialized training and leverage extensive cross-functional expertise, is rapidly expanding. The EASIGEN-DS project evolves from two EU infrastructure projects that have proven to be very successful in providing access to cutting-edge DNA sequencing technologies to hundreds of researchers. Here, we propose to carry out a design study for establishing a new European Research Infrastructure on Advanced Genomics Technologies, EASIGEN. In order to develop an excellent scientific, technological and operational design, we will conduct landscape studies, stakeholder consultations, and community surveying. In parallel, we will seek for the support and commitment of several national and EU stakeholders and user communities through a multi‐faceted dissemination plan. We envision that EASIGEN will encompass: 1) a Technology Platform that will offer state-of-the-art genomic analysis methods, such as single-cell genomics, spatial genomics and long-read sequencing, as well as population-scale genomics capacity; and 2) a Support Platform that will provide standardization tools, training, co-innovation with industry, and consulting for smaller facilities, including those in widening countries. Both platforms will serve a vast community of users from the health, biomedical and life science fields. The consortium brings together 1) a network of eleven genomics facilities with distinct application specialities. and an aggregated sequencing capacity of >450,000 human genomes per year; 2) four partners with specific and crucial expertise: data stewardship, ethical, legal and social implications, socio-economic impact and innovation. The new infrastructure will strengthen the European Research Area, promote interconnections within the ESFRI landscape, and boost an innovative biotechnology-based industry.

AIOLIA gives a robust 3-tier response to the complex challenges posed by the need to operationally interpret the EU AI Act and global AI regulation. (1) Recognizing the gap between ethical values and their practical application in engineering, AIOLIA pioneers a bottom-up approach to operationalize AI ethics with regard to human condition and behaviour. Following a selection of real-world use cases, AIOLIA translates high-level principles into actionable and contextual guidelines co-created by leading academic, policy, and ethics-aware industrial partners who represent diverse professional and geographic European and international contexts. (2) AIOLIA's commitment to context-sensitivity is deepened by crafting modular, inclusive training materials following the ADDIE methodology designed to cater to diverse learning needs. Hosted on the Embassy of Good Science, AIOLIA materials will range from lectures, videos, and mock reviews to such innovative formats as podcasts, Tiktoks, and a chatbot teaching AI ethics. (3) AIOLIA's outreach is amplified by encompassing 7 research ethics and integrity networks and 3 prominent computer science networks. This strategic alignment enables us to effectively recruit training participants and disseminate human-centric ethics guidelines to a wide spectrum of stakeholders, from ethics experts to early-stage researchers and policymakers worldwide. Resolutely European, AIOLIA's vision propagates beyond EU, embracing global cooperation with leading universities and think tanks in China, South Korea, Japan, and Canada. Utilizing UNESCO platform with its reach to Africa and South Asia, AIOLIA’s guidelines evolve into an analytic toolbox for key international AI dialogues and processes. This global perspective ensures that AIOLIA's impact is not only significant but also sustainable, contributing to fair scientific cooperation and providing concrete and culturally informed ethics instruments to shape the next generation of AI systems.

Plasma accelerators driven by advanced laser sources and/or compact electron linacs are key components for the next generation of green and sustainable research infrastructures. We propose a project on the development of "Plasma Accelerator systems for Compact Research Infrastructures" (PACRI), which will develop highly important and ground-breaking plasma accelerator technologies for Europe's future research infrastructures (RI). The specific objectives of PACRI are: - The development of high repetition rate plasma modules, as required for the EuPRAXIA ESFRI project, capable of extending its scientific scope from high average brightness radiation sources to high energy physics. - Improving the performance of normal conducting accelerator technology for X-band linacs, paving the way for high repetition rate operation (up to kHz) with a focus on efficiency and power consumption. - The development of key laser components required to scale up high power, high repetition rate laser technology as required by the EuPRAXIA and ELI ESFRI research infrastructures. The achievement of the PACRI objectives will enable the production of unique particle and photon beams with a wide range of applications in ultrafast science, high precision medical imaging, materials diagnostics, medical treatment and, in the longer term, the development of future compact colliders. These developments will be used for future resource-efficient upgrades of existing RIs at INFN, Elettra, CERN, CNR, CNRS, DESY, ELI, GSI/FAIR and UKRI. In addition, PACRI will support the implementation of ESFRI's EuPRAXIA distributed research facility by consolidating its sites and centres of excellence being developed under the ongoing EuPRAXIA_PP project. It will fund the development of some technical prototypes that are crucial for the implementation of the EuPRAXIA project and other European Research Infrastructures (e.g. enabling major upgrades to the ELI-Beamlines facility).

MALDIBANK: A Comprehensive Solution to Microbial Challenges In an era marked by pressing environmental and health challenges, including climate change, biodiversity loss, global epidemics, and food security, understanding and leveraging the power of microbes is critical. Microbes, fundamental to the biosphere, impact everything from ecosystem dynamics to human health. However, their vast diversity remains largely underestimated. To harness this potential, precise identification of microorganisms is crucial, especially given their varied implications across different sectors. Over the past 15 years, MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time-of-Flight) mass spectrometry (MS) has revolutionized microbial identification in fields such as clinical microbiology, food safety, environmental monitoring, and sustainable agriculture. Despite its transformative potential, MALDI-TOF MS technology has been underutilized outside clinical microbiology. MALDIBANK emerges as a groundbreaking initiative to extend the reach of this technology, providing innovative solutions for understanding and utilizing microbial diversity for global problem-solving. MALDIBANK is conceptualized as a global, cloud-based, open MALDI spectra databank for the identification of microorganisms, combining a vast spectrum database with advanced algorithmic tools. This databank will facilitate processing, characterization, epidemiological surveillance, and more, embodying Open Science and FAIR data principles. It aims to become a new reference in microbial identification, drawing parallels with the impact of GenBank in genomics. By integrating 100,000 reference spectra with rich metadata and employing deep learning models, MALDIBANK will enhance microbial characterization and support areas like antimicrobial resistance prediction and environmental monitoring. It will serve as a dynamic resource for the global scientific community, enabling the exploration of microbial capabilities an