Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : LAST NEANDERTHALS (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Université de Bologne — Pays : Italie — Rôle : CO-PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 4473145.5 €

Our closest relatives, the Neanderthals, abruptly disappeared 40 thousand years ago (ka) after having endured for 350 thousand years in a territory ranging from the Iberian Peninsula to southern Siberia. Decades-long research attempted to address the cultural aspects and the demographic and environmental factors that triggered their demise. Yet, there are no widely accepted scenarios that satisfactorily explain the extinction of the Neanderthal. These shortcomings are in part because the data available originated from a limited number of sites mainly in western and central Europe, which we now know were peripheral to the range of the last Neanderthals. To compellingly reconstruct the chain of events that led to Neanderthal’s extinction, the scientific community needs new extensive archaeological data, possibly from the core regions of the last Neanderthals’ range. Areas of western and central Asia and eastern and southeastern Europe were at the core of this range, served as gateways to marginal areas, and witnessed Neanderthals’ bio-cultural interactions with Sapiens and Denisovans. For the first time, three PIs with vast expertise on Neanderthals’ culture, biology, and paleoenvironments will synergistically attempt to bridge the knowledge gap between the core and the periphery of their range at the time of their decline between 60-40ka. Project LAST NEANDERTHALS will 1) accurately collect, date, integrate, and model new high-resolution cultural, bio-genetic, and environmental data from understudied areas in western and central Asia and eastern and southeastern Europe; 2) provide an unprecedented perspective on the last Neanderthals’ population dynamics; 3) offer a comprehensive and compelling explanation of the mechanisms that led to their extinction by integrating data from their entire range and formulating and testing nuanced hypotheses using new models and simulations; 4) serve as a proxy for the fate shared by all archaic human groups.

Mots-clés : middle paleolithic,early upper paleolithic,homo sapiens,ancient dna,neanderthal,western and central asia,eastern and southeastern europe
Projet ERC : TASTADE (Horizon Europe, appel 2025, Synergy grants)
Entité participante : Université libre d'Amsterdam — Pays : Pays-Bas — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2450136.25 €

Abstract  From the sixteenth to the nineteenth centuries, slave traders of mostly European origin violently transported more than 12.5 million African men, women, and children to the Americas. This was the largest forced transoceanic migration in human history. Scholars have focussed on the effects of this migration on African and American history, while treating the slave trade’s effects on European societies as marginal. This supposition of marginality stems from two biases in existing research: a focus on the companies and individuals who directly outfitted slaving voyages instead of on the far larger group of people who invested in these voyages, and an over-emphasis on slave trade profits, leaving out many other relevant indicators of the economic, political, and cultural significance of slave traders. The trans-Atlantic slave trade and the development of Europe project (TASTADE) will correct this imbalance by identifying thousands of men and women who financed the slave trade and scrutinizing their embeddedness in their local, regional, national, and transnational contexts, to answer the following research question: How did the investors in the trans-Atlantic slave trade based inside and outside Europe shape the economies, politics, and cultures of Europe? TASTADE will transform existing scholarship by delivering a ground-breaking assessment of the national and trans-national networks that facilitated this trade and by linking these networks to key aspects of European development. In realising this overarching objective, TASTADE will reshape our understanding of the history of capitalism, colonial and commercial politics, and European culture. Our unique pan-European perspective relies on the distinctive synergy of approaches provided by the members of the core research team, who will inscribe the history of the trans-Atlantic slave trade fully into the story of European development and help European society confront, disclose, and memorialise the sl

Mots-clés : slavery,slave trade,trading companies,prosopography,investment,transnational analysis,legacies of empire
Projet ERC : OCEAN (Horizon Europe, appel 2022, Synergy grants)
Entité participante : Université de Durham — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Until recently, most of the major advances in machine learning and decision making have focused on a centralized paradigm in which data are aggregated at a central location to train models and/or decide on actions. This paradigm faces serious flaws in many real-world cases. In particular, centralized learning risks exposing user privacy, makes inefficient use of communication resources, creates data processing bottlenecks, and may lead to concentration of economic and political power. It thus appears most timely to develop the theory and practice of a new form of machine learning that targets heterogeneous, massively decentralized networks, involving self-interested agents who expect to receive value (or rewards, incentive) for their participation in data exchanges.  OCEAN will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making agents, including uncertainty quantification at the agent's level. OCEAN will study the interaction of learning with market constraints (scarcity, fairness), connecting adaptive microeconomics and market-aware machine learning.  OCEAN builds on a decade of joint advances in stochastic optimization, probabilistic machine learning, statistical inference, Bayesian assessment of uncertainty, computation, game theory, and information science, with PIs having complementary and internationally recognized skills in these domains. OCEAN will shed new light on the value and handling of data in a competitive, potentially antagonistic multi-agent environment, and develop new theories and methods to address these pressing challenges. OCEAN requires a fundamental departure from standard approaches and leads to major scientific interdisciplinary endeavors that will transform statistical learning in the long term while opening up exciting and novel areas of research.

Mots-clés : machine learning,federated learning,computational game theory,multi armed bandits,bayesian inference,markov chain monte carlo,multi agent reinforcement learning,online matching markets,data market,incentive
Projet ERC : CHRONOLOGY (Horizon Europe, appel 2024, Synergy grants)
Entité participante : Institut de technologie du Massachusetts — Pays : Etats-Unis — Rôle : PI
Acronyme de l'entité : MIT
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.5 €

Experiencing the world and inferring its causal structure rely on the flexible temporal organization of information in the brain, enabling future planning in thoughts and actions. Understanding how the brain maps events in time is essential, yet surprisingly little is known about the neural mechanisms by which the brain represents time and uses it for computations. Based on the observation that complex neural activity accompanies the mental evaluation of time across species, our project aims at testing the hypothesis that the collective dynamics of brain circuits involved in memory generate and organize representation of temporality. To identify the key structures of time representations in the brain, we will record neural activity at different neuroanatomical scales (from neuron to whole-brain) in three species (rodents, non-human primates, and humans) while individuals are behaving in timing tasks of varying cognitive complexity. A geometrical analysis of neural activity will determine the existence of temporal cognitive maps that provide individuals with a mental chronology of experienced events. We will test if the navigation of temporal cognitive maps is involved in tasks where individuals mentally travel in time. Exploiting state-of-the-art artificial intelligence methods to build interpretable recurrent neural network models, we will identify generic processes supporting the emergence of time representations by comparing signatures of theoretical mechanisms with brain activity. Targeted causal manipulation at the single cell resolution will help select precise mechanisms among model-based hypotheses, including the role of local and long-range neuronal connectivity in the establishment of circuit dynamics that develop across time scales. Our synergistic cross-disciplinary team will establish an innovative, biologically-grounded, overarching framework for the representation of time in the brain, its dependence on context, and its relation to memory.

Mots-clés : time perception geometry of neural representations cognitive maps multielectrode recordings all optical electrophysiology acousto optic two photon calcium imaging recurrent neural network models computational neuroscience neural dynamics
Projet ERC : REVEAL (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Institut de technologie du Massachusetts — Pays : Etats-Unis — Rôle : PI
Acronyme de l'entité : MIT
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2864431.0 €

For millennia people have wondered, “Do other Earths exist?” “Are they common?” “Would they show signs of life?”. We now have the technical capability to answer these questions. New radial-velocity spectrometers are capable of detecting the reflex motions of stars hosting Earth-mass planets in their habitable zones; the James Webb Space Telescope has the power to probe the atmospheres of rocky exoplanets. Yet the unprecedented precision of these instruments’ measurement capabilities is up against a fundamental astrophysically-imposed barrier to achieving these goals: contamination of exoplanetary signals by stellar activity and variability. Further progress is contingent on solving this “variability problem”.  REVEAL gathers world-leading experts in exoplanetary and stellar physics to tackle this problem in synergy:  - We will build on recent advances in magnetohydrodynamic simulations of stellar atmospheres, and data-driven efforts to separate the exoplanet signal from the stellar variability.  - We will simulate the “ground truth” of the turbulent physics of entire stellar photospheres resolved at the level of individual convective cells for a broad class of stars.  - We will model the emergent spectra of these “virtual” stars and “observe” them using the same data-processing pipelines as stellar radial-velocity and transit-spectroscopy observations.  We will continue to observe the Sun and stars hosting small planets found with TESS and PLATO. The stars’ own spectra will REVEAL the clues needed to disentangle stellar variability from our measurements of their planets’ masses and the fingerprints of molecules in their atmospheres. Our unified efforts will enable the new cutting-edge space observatories and ground-based facilities to realize the full potential of their designs, bringing us closer to the most profound discoveries we could hope to achieve in our lifetimes - the identification of another Earth or even possible signs of life on another planet.

Mots-clés : detection and characterization of exoplanets habitability of exoplanets stellar activity stellar variability
Projet ERC : NEMESIS (Horizon Europe, appel 2022, Synergy grants)
Entité participante : Don Carlo Gnocchi Foundation — Pays : Italie — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 320000.0 €

Focal brain disorders, including stroke, trauma, and epilepsy, are the main causes of disability and loss of productivity in the world, and carry a cumulative cost in Europe of about 500 billion euro/year. Now, physicians diagnose and treat these conditions as if they were caused by local dysfunction due to the pathological process. However, there is growing evidence that, in most neurological and psychiatric disorders, clinical symptoms reflect widespread network abnormalities. Normalization of such network abnormalities through “circuit-based” stimulation would therefore improve function. However, this form of therapy is currently limited by numerous factors: lack of knowledge about the underlying mechanisms and their behavioural relevance; inability to map these abnormalities onto single patients; and, most importantly, a principled understanding of where and how to stimulate the brain to produce functional recovery. ‘NEMESIS’, from Ancient Greek as “give what is due”, aims to “give an injured brain what is missing”, i.e., restore through stimulation normal activity in dysfunctional brain circuitries. By synergizing people, concepts, and technologies, NEMESIS will first characterize the effects of focal injury at multiple spatial and temporal scales (from whole brain to local circuits). Through the combination of observational (e.g., fMRI, EEG, calcium imaging, LFPs) and causal methods (e.g., electro-magnetic stimulation, optogenetics) NEMESIS will test the hypothesis that disconnected networks lie in a “sleep-like state” that impairs communication. Thirdly, NEMESIS will create whole brain models of structure/function to predict the effect of individual lesions and simulate novel stimulation protocols aimed at “re-awakening” the disconnected brain. Finally, proof-of-concept interventions that combine circuit-based stimulation and behavioural training, guided by modelling and animal studies, will be tested to restore normal activity, and so give back what is due.

Mots-clés : focal injury,brain networks,brain rhythms,sleep,slow wave oscillations,whole brain computational models,brain stimulation,brain connectivity,fmri,eeg,lfp,calcium imaging,tms,7t mri
Projet ERC : i2B (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Centre norvégien de recherche — Pays : Norvège — Rôle : PI
Acronyme de l'entité : NORCE
Type d'entité : Recherche
Financement ERC de l'entité : 3204125.0 €

The Arctic Ocean is turning blue. Abrupt Arctic warming and amplification is driving rapid sea ice decline and irreversible deglaciation of Greenland. The already emerging, substantial consequences for the planet and society are intensifying and yet, model-based projections lack validatory consensus. To date, we cannot anticipate how a blue Arctic responds to and will amplify an increasingly warmer future climate, nor how it will impact the wider planet and society. Climate projections are inconclusive as we critically lack key Arctic geological archives that preserve the answers. This “Arctic Challenge” of global significance can only be addressed by investigating processes, consequences, and impact of past “greenhouse” (warmer than present) states. The timeliness of i2B is tied into retrieval of revolutionary, new Arctic geological archives of past warmth and key breakthroughs in climate model performance that will be integrated in a concerted framework beyond state-of-the-art. i2B will deliver a ground-breaking, synergistic framework to answer the central question: “Why and what were the global ramifications of a “blue” (ice-free) Arctic during past warmer-than-present-climates?” This will be addressed through three connected, cross-disciplinary objectives integrating the expertise, knowledge, and skill-sets of three PIs and their different Arctic paleo-climate and modelling teams. i2B will quantify cryosphere (sea ice, land ice) change in a warmer world (O1) that will form the scientific basis for understanding the dynamics of Arctic cryosphere and ocean changes (O2), to enable quantitative assessment of the impact of Arctic change on ocean biosphere, climate extremes and society (O3) that will underpin future cryosphere-inclusive IPCC assessments. i2B will solve the “Arctic Challenge” with the synergistic multiplier of the 3 PIs` expert capabilities providing pioneering knowledge on how a blue Arctic impacts Earth’s climate during greenhouse climate states

Mots-clés : arctic ocean,greenhouse climate
Projet ERC : HEAVYMETAL (Horizon Europe, appel 2022, Synergy grants)
Entité participante : GSI Helmholtz Centre for Heavy Ion Research — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : GSI
Type d'entité : Autres
Financement ERC de l'entité : 2248863.0 €

The incredible density, gravity, and electromagnetic field strengths of neutron stars (NS) make them laboratories for physics under extreme conditions. But probing these exotic objects is difficult. With the 2017 gravitational wave detection of a NS-NS merger, the landscape changed, and we can now get high-quality spectra of the decompressed neutron-rich matter emerging from the collision. This is a new transient astrophysical phenomenon called a 'kilonova'. Kilonovae are a potential treasure trove of information on some of the biggest open questions in physics: understanding the nuclear and astrophysical pathways that created half of all the heavy elements (Z > 30) in the universe, and the physics of very hot and extremely dense matter. For this reason, they are considered a scientific priority and kilonova science is the target of several large new and upgraded facilities. But kilonovae are challenging: the phenomenon is short-lived, requiring rapid follow-up with large telescopes, the outflow is heavy element-dominated making it extremely demanding to model, and the merger itself covers a huge dynamic range and involves complex nuclear physics. To interpret the spectra we require new atomic data, which does not yet exist for most of the heavy elements. To tackle these challenges, HEAVYMETAL assembles experts in astrophysical observations, hydrodynamical merger simulation, numerical radiative transfer, and laboratory heavy element spectroscopy and atomic structure calculation. With this team we will be able to determine the structures and overall geometries of the merger outflow, the elemental abundances, and their stratification within the ejecta. By the full exploitation of kilonovae we will trace the nucleosynthesis pathways in NS mergers, and provide important insights on heavy nuclei, neutrino interactions, and the nature of high-density matter, and we will chart the role of compact object mergers as the cosmic forge of the heaviest elements.

Mots-clés : neutron stars kilonova radiative transfer laser produced plasma spectroscopy heavy ion spectroscopy gravitational waves r process origin of the elements
Projet ERC : EUROpest (Horizon Europe, appel 2024, Synergy grants)
Entité participante : Institute of Geography and Spatial Organization, Polish Academy of Sciences — Pays : Pologne — Rôle : Partner
Acronyme de l'entité : IGSO PAS;IGiPZ PAN
Type d'entité : Recherche
Financement ERC de l'entité : 421250.0 €

Born from years of interdisciplinary collaboration, EUROpest aims to articulate the complex ways in which social-ecological systems shape epidemics. It builds on resilience and actor-network theories to advance its own eco-bio-social paradigm that embraces a multi-causal understanding of disease transmission and disease impacts on human societies and ecosystems. While striving to develop and validate a general theoretical model, it takes the well-documented and highly diverse world of late medieval and early modern Europe as its laboratory – investigating its interconnected climatic, cultural, demographic, economic, ecological, and pathogenic history. With regard to the latter, EUROpest assumes malaria, smallpox, tuberculosis and enteric diseases were major components of a disease baseline over which the most devastating disease, plague (Y. pestis), occurred. EUROpest will carry out regional case studies – from Spain to Lithuania, Greece to England – selected on the basis of available and procurable written, scientific and archaeological data. It will holistically consider the contexts of plague outbreaks identified in those regions, to understand how context both facilitated outbreaks and also shaped them, and their short- and medium-term impacts. EUROpest combines archival source analysis with archaeology, archaeogenetics, paleoecology and paleoclimatology, and subjects case studies to novel human-supervised machine-learning to identify the causal role of factors influencing regional outbreaks. As the contemporary imagination is guided in its understanding of epidemic disease by the outbreaks of the past, EUROpest’s contribution will be critical to developing more nuanced and realistic scenarios of future pandemics, academic as well as popular. With EUROpest PIs already engaging policy makers, the mathematical precision of the eco-bio-social analysis EUROpest proposes will help design more successful and targeted interventions for future pandemic response.

Mots-clés : adna studies,palaeogenomics,environmental history,interdisciplinary history,disease history,climate history,plague,smallpox,machine learning in historical applications
Projet ERC : 4D-BioSTEM (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Université Louis-et-Maximilien de Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499375.0 €

Electron Microscopy (EM) has transformed research in the Life and Physical Sciences separately. Cryo-EM in Life Sciences allows the 3D structure determination of proteins down to 1.0 Å resolution in case they are large enough and present in high numbers in homogeneous states. For many molecules involved in diseases like neurodegeneration, however, structure determination is still severely hampered due to their insufficient contrast when imaged in vitreous ice or in their native cellular environment. To date, EM in the Physical Sciences generated utmost contrast for light atoms and established a resolution in the range of 0.2 Å limited only by thermal motion. This record was achieved by evolving scanning transmission EM (STEM) from a 2D to a 4D imaging technique combining imaging with diffraction. In this project, we will work out 4D-BioSTEM methodologies and develop a cryo-EM tool that maximizes contrast and resolution by bringing together EM groups from Life and Physical Sciences. 4D-STEM imaging of frozen biological specimens will be approached with unique and specialized hardware, theory and simulation, the development of microscope operation routines, and image reconstruction algorithms. In particular, we will acquire sparse 4D data using ultrafast detectors, employ methods for direct phasing (differential phase contrast, DPC) and establish advanced, so-called ptychographic, techniques to gain maximal signal from noisy 4D cryo-STEM data that are limited in their electron dose budget. We will make use of synergies between recently separated fields in order to make proteins smaller than 50 kDa amenable to structure elucidation. Furthermore, we will expand 4D-STEM to tomography, to obtain high-contrast 3D reconstructions from cellular samples, human brain tissue of neurodegenerative diseases, and vitrified organic energy materials. A new comprehensive structural imaging framework will be put forward and benchmarked as to its utility in Life and Physical Science applications of cryo-EM.

Mots-clés : electron microscopy,cryo em,stem,scanning transmission electron microscopy,phase contrast imaging,image processing,automation,imaging neurodegeneration