Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : UNEQUALWITHIN (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Université de Stockholm — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1914140.0 €

To understand and mitigate economic inequalities, both locally and globally, we need to acknowledge inequalities within households. Yet, in most empirical studies, such intra-household inequalities are disregarded mainly because we lack appropriate measurement tools and data. Not only is this problematic for inequality measurement, this lack of understanding hampers the design of cost-effective poverty reduction and child development policies. This project has five general objectives. First, I will update the facts about inequalities through direct measurement of intra-household consumption allocations, and relate these to spousal income contributions. Second, I will develop and validate novel measures of parental resource-allocation preferences and use these to study whether children are likely to benefit more if mothers, rather than fathers, receive cash transfers. Third, I will develop and validate novel measures of household decision-making and use these to investigate how targeted transfers shape women’s empowerment. Fourth, I will study whether cash transfers or an educational parenting program is most cost-efficient for child development. Fifth, I will use an integrated framework and the new tools and data, to refine our understanding of the mechanisms behind inequalities among adults and child development. Concretely, the project will contribute to our knowledge in the following specific ways. I will carry out an extensive data collection on intra-household allocations, parental-allocation preferences and women’s empowerment, in ten very diverse countries, one from each decile of the world income distribution. I will engage in a local RCT in Tanzania on cash transfers and parenting, which also involves extensive data collection on household consumption, time use, preferences and decision-making. Finally, I will conduct lab experiments in Chile, India and Tanzania so as to validate the parental-allocation preference and decision- making measures.

Mots-clés : inequality,households,child development,gender equality
Projet ERC : UNEARTH (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Société Max-Planck pour le développement des sciences — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : Société Max Planck
Type d'entité : Recherche
Financement ERC de l'entité : 531755.5 €

Humans and other living beings are constantly shedding DNA, and this DNA is preserved in archaeological sediments. In 2021, I developed the first methods for reliably capturing and analyzing human nuclear ancient DNA (aDNA) from sediments, leveraging this abundant genetic resource as a reliable tracer of biological identity. For ancient societies, such aDNA has the potential to function as forensic “breadcrumbs” that trace the spaces inhabited by ancient individuals. At the well-documented, multi-phase Early Bronze Age settlement of Vráble, I will undertake a cutting-edge research program to obtain human aDNA from over 100 individual house floors, spanning the entire occupational area and 500-year history of the settlement. The UNEARTH project will reveal inheritance patterns and social organization, and map individuals from the cemetery back onto the spaces where they left their genetic traces. By integrating genetic, bioarchaeological, and isotope analyses, UNEARTH seeks to uncover socioeconomic stratifications and their role in prehistoric neighborhood organization. The methods developed in UNEARTH for extracting and analyzing human aDNA from sediments will have wide-ranging impact on archaeogenetics, enabling new analyses on archaeological sites, cultures and time periods that lack associated human remains. Crucially, UNEARTH will develop a robust framework for using human aDNA from sediments in cases where bones cannot be ethically sampled. By establishing new methodology and best practices for sampling and analyzing sediment aDNA, this project will unlock rich genetic records that are ubiquitous at nearly every archaeological site in order to elucidate the lived experiences of prehistoric Europeans at unprecedented resolution.

Mots-clés : bronze age,population genetics,social organization,sediment dna,ancient dna
Projet ERC : NOVELTEETH (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 2651590.0 €

One long-standing question in evolutionary biology is: how do new morphological innovations arise? Integrative advances in palaeontology, genomics, development and evolution have unveiled general principles behind evolutionary novelties. However, we are far from understanding the mechanisms by which novelties emerge from ancestral genomic and developmental programs and then diversify in new ecological contexts. To solve this problem, my research uses the dramatic morphological and ecological diversity of bat teeth as a model system to study the origin and diversification of a major mammalian innovation, the tooth classes. Using morphological, genomic, developmental and modelling approaches on multiple species of bats from various ecological contexts, my goal is to understand the origin of mammalian tooth classes and establish a predictive model to study their evolution. Using geometric morphometric approaches, I will first characterize the differences and unique traits in tooth class morphologies in adults and during ontogeny on µCT scans (Aim 1). Then, to link the morphological variation with the underlying changes in the genomic and developmental program, I will establish a developmental transcriptomic signature for each tooth class using Spatial Transcriptomics and MERFISH in multiple species across developmental stages (Aim 2). Finally, I will link these morphological and transcriptomic changes by developing an integrative data-driven model of tooth class evolution using machine learning and extend these models to other mammals (Aim 3). By establishing bat teeth as a unique study system, my research constitutes an integrative framework using natural variation as a starting point to understand the evolution of morphological novelties in various ecological contexts.

Mots-clés : novelties,eco devo devo,morphological evolution,teeth,deep homology
Projet ERC : FemtoMagnet (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 2499926.0 €

While the electronic industry has successfully entered the nanoworld following Moore’s law, the speed of manipulating and storing data lags behind, creating the so-called ultrafast technology gap. Processors already have a clock speed of a few gigahertz, while the storage on a magnetic hard disk requires a few nanoseconds. This bottleneck can also be found in magnetic random access memory devices. The use of ultrafast pulses of light has demonstrated effectiveness in manipulating magnetic orders on very short time scales. However, the physical processes involved are still poorly understood, and such a control reaches the micrometer scale at best, effectively preventing their use for high-density data storage. FemtoMagnet aims to develop an entirely new approach to manipulating magnetic domains based on the engineering of plasmonic nanodevices. For that, these devices will optically generate ultra-short, intense, and reversible pulses of magnetic field at the nanoscale, a challenge that no other technique can achieve so far. To meet its ambitious goals, my research program engineers innovative plasmonic nanostructures inversely-designed to tailor light-matter interactions at the nanoscale. Under the right illumination conditions, the electromagnetic fields generated by the nanostructure set the electrons in a metal (such as in a coil) in pseudo-continuous drift motion, in turn yielding the creation of a strong stationary magnetic field. By specifically creating and manipulating ultrafast, strong, confined and reversible pulses of magnetic field in an all-optical fashion, my research program will enable the manipulation of magnetic domains at the nanoscale and over very short timescales (a few tens of femtoseconds), opening the way to applications in ultrafast data storage and data processing.

Mots-clés : nanophotonics,ultrafast and intense pulses of magnetic field,plasmonic nano antennas,light matter interactions,magnetic field and matter interactions,ultrafast data storage
Projet ERC : LANGUAGE REDUX (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1974676.0 €

The LANGUGE REDUX project addresses the continuing challenge of understanding the processes that have shaped linguistic diversity. Aiming to push deeper into linguistic prehistory, the main questions it will be concerned with are: How did languages come to be distributed the way they are, and can we identify parts of the world where particularly old linguistic distributions are preserved? The project will harness tools from geography and macroecology to pursue a radically new, strongly data-driven approach to explore these questions: while historical linguistics has traditionally focused on language spread and language expansion, the LANGUAGE REDUX project will instead turn to the processes in which the range of languages is reduced before they are ultimately replaced by other languages. It will explore the commonalities of the places in which languages survive later waves of language expansion longest –so-called REDUX areas–, and derive an account of geographical factors that favor the conservation of old linguistic distributions from them. The project’s main aim is to test the Geospatial Layering Hypothesis, which states that we can extrapolate from REDUX areas to identify those parts of the world that preserve earlier linguistic distributions, hosting deep lineages and typological structures that were once more common generally. If confirmed, this would be a breakthrough in historical linguistics and open up perspectives on linguistic and population prehistory that are hitherto unavailable. To explore this, the LANGUAGE REDUX project will establish a research framework in which qualitative historical evidence on different time scales is engaged with spatial statistics, process-based quantitative modeling, and state-of-the-art typological methods; in addition, the framework will take into account genetic evidence as a proxy for demographic prehistory and thereby embed the LANGUAGE REDUX project in an interdisciplinary research landscape on human prehistory.

Mots-clés : language geography,linguistic diversity,language dispersal,linguistic and demographic prehistory
Projet ERC : UMCMC (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : École supérieure des sciences économiques et commerciales — Pays : France — Rôle : PI
Acronyme de l'entité : Essec
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

This project develops a statistical toolbox for the approximation of probability distributions that commonly arise in data analysis. The problem of approximating probabilities arise in many tasks of data science: in Bayesian statistics and its many variants, in classical hypothesis testing with p-values, in likelihood-based methods when the model involves latent variables, in models with intractable likelihoods, in the construction of knockoffs for principled variable selection, for example. State-of-the-art methods for such approximations include Markov chain Monte Carlo (MCMC), where a Markov chain is generated in such a way that it converges to the probability of interest as the length of the sequence goes to infinity. This stands at odds with modern developments in computing hardware, which provide an increasing number of parallel processors, but where each process has a stagnating clock speed. Methods that are amenable to parallel computing must emerge to help scientists in all fields to make the most of their data. The project builds upon a framework called Unbiased Markov chain Monte Carlo (UMCMC), in which accuracy improves arbitrarily with the number of parallel runs. Each run involves the generation of coupled Markov chains for a random time horizon.  Part 1 develops UMCMC to realize its potential as a comprehensive basis for probabilistic computation on modern hardware. The project includes theoretical analyses of cost and measures of efficiency, and methodological innovations towards adaptive, efficient, robust and convenient computation.  Part 2 contributes to the applicability of UMCMC, by conceptualizing the design of coupled Markov transitions, and considering a number of challenging settings: distributions supported on submanifolds and their application in economics, distributions on graphs and their applications in the fight against malaria, and Bayesian nonparametric models for cell type deconvolution from transcriptomics data.

Mots-clés : monte carlo numerical integration probability coupling parallel computing
Projet ERC : K9VocLearn (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université Loránd Eötvös — Pays : Hongrie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2573296.0 €

Modifying the vocal repertoire using an external auditory model is a prerequisite for speech production. But how full-fledged vocal learning evolved in humans, uniquely among primates, is still unclear. Integrating recent evidence from ethology and genetics, I hypothesize that selection for tameness, alloparental behavior and cooperativity in concert were the key driving processes for the emergence of human vocal learning and speech. I propose that dogs constitute an ideal model to test this hypothesis as they underwent a strong selection for tameness and cooperativity with, and often alloparented by humans; at the same time, their vocal behavior markedly changed compared to their closest relatives, the wolves. Dogs have control over their vocalizations, suggesting the presence of some primordial forms of vocal learning abilities. Combining bioacoustics, ethology, genetics, and brain imaging, K9VocLearn thus sets out to reveal the mechanisms underlying the emergence of vocal learning capacities in dogs. Specifically, I test how genetic similarity with wolves, particular gene variations of breeds, extreme domestication-syndrome phenotype, and individual cooperativity affect abilities and neural processes involved in vocal learning. WP1 utilizes citizen science, bioacoustics and machine learning approaches to develop a comprehensive catalogue of dogs’ vocal repertoire. WP2 seeks evidence of vocal usage and vocal production learning, including vocal imitative abilities in dogs, while also testing neural and vocal control mechanisms involved. WP3 tests dogs’ vocal coordination abilities in con- and heterospecific interactions both on the behavioral and the neural level. In early intervention experiments, WP4 longitudinally examines vocal ontogeny and the role of the acoustic environment in vocal flexibility. Breaking ground on capturing the emergence of vocal learning in a cooperative domestic species, K9VocLearn will provide new insights into human language evolution.

Mots-clés : vocal learning language evolution domestication cooperativity bioacoustics dog behavior vocal communication vocal development functional magnetic resonance imaging event related potentials optical imaging sound recording
Projet ERC : ExoMagnets (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : Commissariat à l’énergie atomique et aux énergies alternatives — Pays : France — Rôle : PI
Acronyme de l'entité : CEA
Type d'entité : Recherche
Financement ERC de l'entité : 1992863.0 €

The research in exoplanetary sciences has skyrocketed since the first discovery of planet 51 Peg b by Mayor and Queloz (1995). More than 5200 exoplanets have been discovered since and have revolutionized our understanding of how star-planet systems are formed and evolve. More and more exoplanets keep being discovered today, and their characteristics and that of their host star are being precisely determined using space-based and ground-based multi-wavelengths observations. Nevertheless, we are still blind to a fundamental aspect of exoplanets: what kind of magnetism and magnetosphere do they possess? On Earth, we know the magnetic field shields the atmosphere from the space environment and has been essential to maintaining life as we know it. With the advent of the SKA Observatory, we expect to detect magnetospheric radio signals from hundreds of exoplanets. These magnetospheres also lead to star-planet magnetic interactions for about a third of the known exoplanets, which leave observable traces on the activity tracers of the host star. However, such detections are not enough by themselves to quantify the magnetic properties of exoplanets due to an incomplete theoretical understanding of magnetic interactions. In ExoMagnets we will therefore address the following science questions: how planets interact magnetically with their environments? How much energy can be involved, and what observational tracers can be detected? What type of magnetism can be sustained by an Earth in the habitable zone of a low-mass star? We will address these questions by filling out the present theoretical gaps about the magnetic coupling between an exoplanet and its local environment. We will quantify for the first time its energetics, its observable multi-wavelength spectrum, and leverage them to constrain the magnetism of exoplanets on short-period orbit. These approaches will be combined to provide the theoretical tools to characterize the magnetism of a large sample of exoplanets.
Projet ERC : P-BOT (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed Matter Physics
Entité participante : Commissariat à l’énergie atomique et aux énergies alternatives — Pays : France — Rôle : PI
Acronyme de l'entité : CEA
Type d'entité : Recherche
Financement ERC de l'entité : 1941033.0 €

The ocean absorbs 90% of the heat associated with global warming and 30% of anthropogenic CO2. How such tracers are accumulated and redistributed within the turbulent ocean is a central issue of long-term climate prediction. The challenge stems from the existence of ocean mesoscale eddies: turbulent vortices tens of kilometers wide that are not resolved by climate models despite being key contributors to ocean transport. In the absence of a better theory, the associated transport is parameterized in global models using ad hoc coefficients with arbitrary depth dependence. The present project will improve upon this unsatisfactory state of the art. Based on a multi-method approach combining theory, laboratory experiments, numerical simulations and satellite data analysis I will derive a physically-based parameterization for turbulent transport in the 3D ocean. The derivation hinges on my recent quantitative theoretical advances for the magnitude and 3D structure of turbulent transport in the canonical models of oceans and atmospheres (the Charney, Eady and Phillips models): - I will augment these theories by including the additional physical ingredients of the real ocean: bottom slope, arbitrary large-scale flow and density stratification, etc. - I will determine the frictional dissipation on the ocean floor by combining rotating-platform laboratory experiments with 3D-printed realistic ocean-floor topography. - I will infer transport and bottom friction independently through the combination of satellite and profiler data. - I will derive the resulting parameterization using multiple-scale expansion before implementing it in a state-of-the-art climate model.  As opposed to the current practice of adjusting transport coefficients to the current state of the ocean, the physically-based parameterization will remain valid in a warming climate, a necessary condition both for paleoclimate studies and for reliable climate forecast over the coming centuries to millennia.
Projet ERC : Heartbeat (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Université technique de Rhénanie-Westphalie à Aix-la-Chapelle — Pays : Allemagne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 184521.0 €

Generating 3D in vitro functional tissues and organs in the millimeter scale remains an unmet dream of modern medicine. Irrespective of great efforts in the field of tissue engineering to design injectable/pipettable hydrogels or implantable/non-pipettable scaffolds for 3D cell growth, it is not yet possible to generate functional and personalized tissues with native-like structures and mature blood vessels. The main reason for this limitation is that current materials do not recapitulate the complexity and dynamics of the native cell environment. To create personalized human tissues, patient-derived induced pluripotent stem cells can differentiate in any cell type but controlling stem cell expansion, differentiation, and organization inside the same 3D scaffold is not possible up to now, as it requires biomimetic and interactive materials beyond simple hydrogels. HEARTBEAT will break with traditional ways to make 3D biomaterials by assembling and crosslinking a variety of unique pre-programmed, rod-shaped, and interactive microgels instead of molecular building blocks. The main aim is to achieve macroporous, aligned, actuatable, and on-demand degradable constructs after automatically pipetting/mixing different microgels and cells, which is not possible with conventional hydrogels. A compatible high-throughput system will be used to screen the innumerable combinations of design parameters to systematically study (stem)cell-material and cell-cell interactions to grow complex tissue. In HEARTBEAT, I will focus on using the interactive bottom-up microgel assemblies to generate millimeter-scale vascularized beating heart tissues. The project will elucidate how material properties, architectures, and actuation affect human heart tissue formation and vascularization and how the construct has to adapt to the growing tissue over time to provide the right extracellular environment.

Mots-clés : microgels,cardiac tissue,induced pluripotent stem cells,vasculogenesis,hydrogels,tissue engineering,in vitro tissue models,high throughput screening,hts