Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : KinSocieties (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université de Turku — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499971.0 €

Social interactions can improve support, resources and protection, but can also increase disease, stress and conflict. Consequently, for group-living species inc. humans, traits as diverse as personality, residence patterns, family-living and disease resistance all evolve in response to pros and cons of sociality. However, the direct links between sociality, health, fitness outcomes and ultimately natural selection are not well-known. KinSocieties reveals, for the first time, the benefits and costs of sociality accrued by individuals and whole societies in two complementary study species - humans and Asian elephants - facing current drastic changes in social structures due to break-down of kin networks. I use rare longitudinal data and two previously unstudied natural experiments to investigate effects of translocation to new social environments, addressed in 6 WPs:  How have human social networks transformed with the modernisation of societies and associated with reproduction, cause of death and lifespan at different times? How does population structuring in humans affect reproduction, cause of death and lifespan? How does population structuring in Asian elephants affect reproduction, cause of death and lifespan? How is translocation to new area with/without kin or friends in humans related to subsequent integration, social networks, reproduction, lifespan and cause of death? How is translocation to new working units with or without kin, friends or social group in Asian elephants associated with stress, health, and friendship formation? Synthesize the costs & benefits of dynamic social structures in a modelling framework  This research boldly combines approaches from social sciences, conservation, evolutionary demography and biology. The results have key theoretical and practical consequences, making also critical contributions to public health by revealing concrete costs and benefits tied to social relationships and their changes in the rapidly changing world of today.

Mots-clés : kin,social networks,societal change,family,natural selection,lifespan,health,reproductive success,infectious disease,human,asian elephant
Projet ERC : CALIX (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : Dartmouth College — Pays : Etats-Unis — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 110012.5 €

Global sea levels will continue to rise as ice sheets shrink in response to climate change, but predictions vary widely on how much ice will be lost in different carbon futures. The single largest source of uncertainty is iceberg calving rates. Calving can cause more rapid ice loss than any other process, but no reliable method currently exists for representing calving in numerical models. CALIX seeks to find and apply the elusive universal calving law, by adopting a radical new approach based on the self-organising nature of glacier systems. The calving law will be formulated using bulk statistical properties of calving events, and will be rooted in both detailed observations and sound theory. The calving law will be implemented in leading ice-sheet models, throughly tested, and used in model run ensembles to determine the most-probable Antarctic Ice Sheet contribution to sea level into the 22nd Century under different mitigation and business-as-usual carbon scenarios. CALIX will address a major knowledge gap in glacier science, and will revolutionise our ability to understand ice-sheet stability, predict ice-sheet response to climate change and anticipate the global consequences.

Mots-clés : ice sheet model,iceberg calving,calving law,greenland,antarctic ice sheet
Projet ERC : FAME (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Université de Brême — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499063.0 €

The realization of computational models for accomplishing everyday manipulation tasks for any object and any purpose would be a disruptive breakthrough in the creation of versatile, general-purpose robot agents; and it is a grand challenge for AI and robotics. Humans are able to accomplish tasks such as “cut up the fruit” for many types of fruit by generating a large variety of context-specific manipulation behaviors. They can typically accomplish the tasks on the first attempt despite uncertain physical conditions and novel objects. Acting so effectively requires comprehensive reasoning about the possible consequences of intended behavior before physically interacting with the real world. In the FAME project, I will investigate the research hypothesis that a knowledge representation and reasoning (KR&R) framework based on explictly-represented and machine-interpretable inner-world models can enable robots to contextualize underdetermined manipulation task requests on the first attempt. To this end, I will design, implement, and evaluate FAME (Future-oriented cognitive Action Modelling Engine), a hybrid symbolic/subsymbolic KR&R framework that will contextualize actions by reasoning symbolically in an abstract and generalized manner but also by reasoning with “one’s eyes and hands” through mental simulation and imagistic reasoning. Realizing FAME requires three breakthrough research results: (1) modelling and parameterization of manipulation motion patterns and understanding the resulting effects under uncertain conditions; (2) the ability to mentally simulate imagined and observed manipulation tasks to link them to the robot’s knowledge and experience; and (3) the on-demand acquisition of task-specific causal models for novel manipulation tasks through mental physics-based simulations. To assess the power and feasibility of FAME, I will use open manipulation task learning as a benchmark challenge.
Projet ERC : StarDance (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : National Institute for Astrophysics — Pays : Italie — Rôle : PI
Acronyme de l'entité : INAF
Type d'entité : Recherche
Financement ERC de l'entité : 2492250.0 €

Thanks to their ubiquity, brightness, and the fact that they are made of stars with similar properties, star clusters have been used as astrophysical laboratories or test particles in an impressive range of research domains. However, we still do not understand fundamental details of their formation and evolution. In spite of recent technological progress, a list of unsolved problems and apparently isolated mysteries has been accumulating over time, some standing since decades.  Among them, the existence of multiple stellar populations in globular clusters, with different chemistry, has challenged generations of researchers. They are not the result of classical galactic chemical evolution, mostly mediated by supernovae, and they jeopardize the use of clusters as simple stellar population templates for extragalactic studies.  Given the mounting problems faced by the most favored scenarios to explain multiple populations, I think it is now time to revisit the foundations of our current thinking. New results by my team and by others show that: (i) the peculiarities in the chemistry of multiple populations are not limited to the oldest globular clusters; (ii) they can be transient in the evolution of individual cluster stars; and most importantly (iii) binary interactions and fast stellar rotation cannot be neglected in the study of star clusters and do have the capability to produce the observed chemistry.  With StarDance I will test a very different scenario, based on a new hypothesis: that multiple stellar populations and five other non-canonical stellar populations (extreme horizontal branch stars and hot sub-dwarfs; extended main sequence turn-offs; red stragglers and sub-subgiants; lithium rich- stars; and blue stragglers) are caused by the interplay between stellar rotation and binary interactions, that are greatly enhanced in the special environment of star cluster, with spectacular results.

Mots-clés : techniques spectroscopic surveys stars abundances stars binaries stars rotation galaxy globular clusters galaxy open clusters and associations galaxy abundances
Projet ERC : DeepLog (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Neurosymbolic AI (NeSy) is the 3rd wave in AI. It wants to answer the key open question in AI as how to combine learning (2nd wave) and reasoning (1st wave) by integrating logic based AI with deep learning. However, there is only little understanding of the underlying principles and there exist no widely used machine learning tools that support NeSy. This makes the development of learning and reasoning systems extremely hard. What is urgently needed is a paradigm shift in NeSy that focuses on foundations rather than on which system from the ‘alphabet-soup’ scores best on the latest benchmarks. I propose to develop these foundations by identifying key building blocks and demonstrate that they support the integration of knowledge and reasoning into any neural network learning task. My methodology is based on the slogan that I have coined:  NeuroSymbolic AI = Neural + Probabilistic + Logical AI  This advocates that we need to integrate the two main paradigms for reasoning (logic and probability), with that for learning (neural networks). I will exploit many similarities I have identified between statistical relational AI, which focuses on probabilistic logics, and NeSy. More specifically, I shall develop the foundations of NeSy. At the conceptual level, I shall identify the building blocks of NeSy by designing primitives that integrate logical, probabilistic and neural networks representations; at the semantic level, I shall introduce the notion of NeSy networks (that encompass logic circuits, algebraic operators and neural networks) as a semantic framework for NeSy; at the computational level, I will show how to exploit NeSy networks for inference and learning. DEEPLOG is not 'yet another NeSy system', but rather a fundamental and operational framework in which a wide variety of NeSy systems and applications can be cast and implemented. We will develop an open-source software environment, and evaluate DEEPLOG ’s generality and applicability.

Mots-clés : learning and reasoning,neurosymbolic ai,statistical relational ai,probabilistic logic programming
Projet ERC : Open SESAME (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2498230.0 €

The goal is to develop a time evolving model for the entire solar atmosphere, including the chromosphere and transition region, based on a multi-fluid description. At present, models are steady, rely on a single-fluid description and include only the corona due to computational challenges. We plan to use time-evolving ion-neutral and ion-neutral-electron models. The multi-fluid approach will enable us to describe the intricate physics in the partially ionized chromosphere and quantize the transfer of momentum and energy between the atmospheric layers. The questions where the solar wind originates and solar flares and coronal mass ejections are driven have both fundamental scientific importance and substantial socio-economic impact. Indeed, the solar atmospheric model is the crucial missing link in the Sun-to-Earth model chain to predict the arrival and impact of CMEs at Earth. What makes this goal now possible is the combination of our implicit solver with a high-order flux-reconstruction (FR) method. The implicit solver avoids the numerical instabilities that lead to strict time step limitations on explicit schemes. The high-order FR method enables high-fidelity simulations on very coarse grids even in zones of high gradients. We will start from this new development and introduce three critical innovations. First, we will combine high-order FR with physics-based r-adaptive (moving) unstructured grids redistributing grid points to regions with high gradients. Second, we will implement CPU-GPU algorithms for the new heterogeneous supercomputers advanced by HPC-Europa. Third, we will implement AI generated magnetograms to make the model respond to the time-varying photospheric magnetic field which is crucial for understanding important properties. We will thus develop a first-in-its-kind high-order GPU-enabled 3D time-accurate solver for multi-fluid plasmas. If successful, we will have the most advanced solar atmosphere model implemented in an operational environment.

Mots-clés : high order methods,gpu enabled,implicit solver
Projet ERC : AuForA (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Université rhénane Frédéric-Guillaume de Bonn — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1956665.0 €

This proposal is at the interface of number theory and automorphic forms and aims at a cross-fertilization of both areas. It focuses on explicit arithmetic problems that can be solved using the full force of the automorphic machinery. Conversely it develops the theory of automorphic forms in higher rank using number theoretic methods.  At the core are three sets of deep and longstanding open conjectures in higher rank cases: - the joint equidistribution conjectures of Michel and Venkatesh concerning the distribution of pairs of shifted CM points, - the “beyond endoscopy” program of Langlands of identifying functional lifts by a comparison of different trace formulae, - the density and optimal lifting conjectures of Sarnak concerning the behaviour of exceptional eigenvalues, and their arithmetic consequences.  The key objects are certain Shimura varieties associated to abelian varieties, higher rank Kloosterman sums, families of L-functions, trace formulae and Hecke eigenvalues. By an interdisciplinary combination of analytic number theory and automorphic forms, the proposal aims at definitive progress and solutions to these three conjectures, each of which has been open for at least 15 years.

Mots-clés : automorphic forms,analytic number theory,trace formulae,equidistribution,l functions,beyond endoscopy,kloosterman sums,density theorems
Projet ERC : REACT (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université fédérale de Rio de Janeiro — Pays : Brésil — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 69933.75 €

We live in a time of endemic uncertainty and accelerating socio-economic exclusion. The collapse of the extractivist ideology of the neoliberal model of development has led to needs for other worldviews. Young people in the Global South are particularly impacted by the socio-economic consequences, affecting their ability to control their livelihoods. This is indicated by high unemployment, gender and job market inequalities, and the decline of living standards despite general economic growth.  REACT emerges as an ambitious, feasible project. The ambition is empirical, methodological and theoretical. REACT uniquely focuses on sourcing everyday activism outside of conventional activist spaces. A qualitative study of 300 youth across 5 cities combined with a survey (12.000) from 20 cities will generate insights on how young people negotiate and act upon their life circumstances. REACT applies a critical-creative pedagogy to foster critical hope via artistic expression, scenario building, urban manifestos, networking and cultural encounters across the Global South. Uncovering individuals’ everyday practices of activism generates insights about the formation of subjectivities in urban contexts, practices of communication in everyday life, perceptions and forms of activism, connects hope with citizenship, and individual action with collective action. These elements are deeply intertwined, hence the need for an interdisciplinary framework. Embedded in communication for social change, and drawing on cultural studies, urban studies, critical pedagogy and critical development studies, REACT will develop a novel interdisciplinary theory for the study of COMmunication, PArticipation and Social Change (COMPAS). REACT’s ambition is also geographical and epistemological; Conducting a study of young people across the geographical Global South can amend the cognitive injustice seen in the imbalance of knowledge production about youth, communication and social change.
Projet ERC : MIGMOBS (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université Waseda — Pays : Japon — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 205313.0 €

MIGMOBS investigates how borders and hierarchies are maintained between “the West and the Rest”, even as those who are internationally mobile sometimes succeed in challenging the “birthright lottery” - i.e. that citizenship at birth most determines someone’s chances in life. It asks: How does changing categorisation of subordinate populations worldwide in terms of “migration”, “free movement”, and “minorities” relate to these in- and between- country inequalities? It echoes critical migration, mobilities and borders scholars who argue that late capitalism in liberal democracies continues to advance through an ever more sophisticated differentiation and management of population – at the border as well as internal to states. Such work, though, has not adequately examined variation regionally, or across historical shifts in political economy: from post-war liberalism, through neoliberalism, to the era of COVID and beyond. MIGMOBS thus explores in unprecedented empirical breadth and detail how states reproduce sovereign power in an otherwise porous world: selecting and extracting wanted or recognised movers as “immigrants”, brutally excluding many other “migrants”, while simultaneously rendering fluid and untroubling a vast range of banal “mobilities” such as tourism and business travel. Mapping physical, virtual and non-human mobilities, the project details demographic and social connections over time between 21 states. This quantitative comparative historical work underpins co-productive ethnographic case studies rethinking a range of archetypal “migration systems” in and from Europe, Africa, Asia and South America. These investigate how subordinate populations resist the categories, statuses and borders imposed upon them. With the pandemic’s impact on border crossings and transactions, new modes of classification and accreditation suggest an increasingly precise biometric control of movement and behaviour: a new phase of late capitalism I call “viral liberalism”.

Mots-clés : migration,mobilities,global inequality,inequalities,development,borders,diversity,liberalism,racism,globalisation,governmentality,transnationalism,decolonial thought,political demography,mixed methods
Projet ERC : RECRUIT (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Université de Twente — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Receptor recruitment occurs in biology as a response to binding, for example, by virus particles to a cell membrane. The interactions that underlie the binding process are typically multivalent in nature, in other words, multiple interactions of the same motif occur simultaneously to provide a collective, cooperative effect. This project aims to employ recruitment as a design criterium for self-assembling building blocks into well-defined architectures. Intrinsically weak and dynamic interactions are essential in achieving self-assembly and recruitment. Exquisite control over stoichiometry and structure of the assemblies is achieved by harnessing ground-breaking developments in the understanding of these multivalent interactions. Follow-up fixation processes will be developed to transfer the molecular organization onto stable building blocks and materials. Functional, e.g., fluorescent, groups will be implemented into the systems to provide insight into recruitment and self-assembly processes. These breakthrough insights will be used tackle challenges with the identification, sensing and isolation of biological particles. High-throughput methods will provide technology to screen multiple virus–glycan combinations with the aim of providing ‘fingerprints’ of viruses based on their binding behaviour. Platforms with nanoscale dimensions and molecular functionalities will be prepared, which will be used for single-particle sensing and particle isolation of, for example, virus particles and extracellular vesicles. As such, this proposal takes inspiration from nature, by borrowing recruitment as a concept to build self-assembled materials, and to contribute to a better understanding of living systems using new detection and isolation tools, with application prospects for biomedical platforms and smart materials.

Mots-clés : self assembly multivalent interactions molecular recognition superselectivity supramolecular interactions at interfaces