Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SEXIPLANTS (Horizon Europe, appel 2022, Starting 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 : 1499940.0 €

The SEXIPLANTS project aims at providing a comprehensive empirical test for plants of the sexual selection theory, and decipher the mechanisms underlying sexual selection in plants. Sexual selection, acting through competition for the access to mates and their gametes, successfully explained numerous reproductive strategies in animals. Sexual selection typically emerges when females produce fewer numbers of larger gametes than males – a situation called anisogamy – which fosters competition among males for accessing the rare ovules. Sexual selection theory should thus be universally valid for all sexually reproducing anisogamous organisms encompassing plants. While the idea that sexual selection acts on plants is largely admitted, most predictions of the sexual selection theory remain untested in the plant kingdom. With a multi-method approach, including experimental evolution in the hermaphroditic plant Brassica rapa and comparative analyses in angiosperms, the SEXIPLANTS project asks:  Q1. Testing the theory. Are fundamental predictions of sexual selection theory valid in the plant kingdom? We will empirically test key predictions of sexual selection theory regarding both male-male competition and female choice processes, and their demographical and genetic consequences.  Q2. Specificity. Does the action of pollinators introduces specificity in the operation of sexual selection? We will empirically test how pollinator behaviour and density can alter sexual selection.  Q3. Perception. Can plants perceive and respond to variation in their mating opportunities? We will empirically test whether plants can plastically adjust the reproductive strategies to variation in competition for access to mates.  SEXIPLANTS will contribute to the development of a uniform and integrative theory of sexual selection valid for sexually-reproducing organisms including plants, and potentially reform our conceptual understanding of plant reproduction, with implications for conservation.

Mots-clés : sexual selection,male male competition,female choice,pollen pistil interactions,condition dependence,pollinator abundances,mating success,experimental evolution,paternity analysis,quantitative genetics
Projet ERC : OneSPIN (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed Matter Physics
Entité participante : École polytechnique — Pays : France — Rôle : PI
Acronyme de l'entité : X
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1913122.5 €

Currently, a great deal of experimental research is dedicated to implement qubits on a wide variety of physical systems. In the last decade researchers have observed optically-active point-defects in 2D materials which serve as single photon sources and present spin-dependent optical emission, making them promising spin-photon interfaces. In parallel, new local probe techniques have been developed to detect magnetic resonance on single atomic spins, and more recently to demonstrate controlled charging and positioning of point-centres in 2D semiconductors. OneSPIN lies at the junction of these very active fields. Inspired by the opportunity that these recent findings bring, I propose to coherently probe single electronic spins localized at point-centres in 2D semiconductors and to engineer their atomic environment. The ultimate goal of this proposal is the demonstration of long spin coherence times for quantum information applications. To achieve this ambitious goal, I will develop a novel approach based on a unique scanning tunnelling microscopy technique which allows for the engineering, excitation and optical detection of single spin resonance. This approach provides a solution to the current lack of tools capable of simultaneously recording the atomic and electronic structure of defects, their optoelectronic response, and the coherence properties of their spins. Using this tool, it will be possible to not only determine the role of the environment on spin coherence, but also to engineer it by deterministically moving localization centres over the surface, creating tailored ensembles of localized spin states. I will use 2D semiconductors which, being chemically stable and “all surface”, are systems which can naturally be addressed, manipulated and engineered using local probe techniques. OneSPIN has the potential to open new opportunities in the fields of material science, quantum information and semiconductor-based quantum technologies.

Mots-clés : quantum technologies,2d materials,electron spin
Projet ERC : HOMESCAPES (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Human Mobility, Environment, and Space
Entité participante : Université d'Utrecht — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498875.0 €

Global South cities have managed public services through socio-technical configurations that provide differentiated alternatives depending on social position. Populations living in low-income neighbourhoods, which in the South accounts for 60–70% of urban housing, seldom have regular access to piped water. They rely on small-scale providers, rain harvesting, and other arrangements. Nevertheless, we do not know much about what happens once the water is transported/stored inside patios, kitchens and other domestic spaces. This is a broader trend: we know little about the socio-ecological life within low-income homes in the urban South. This, despite the fact that it is in these homes that many of the processes sustaining life in the city take place. The question of how socio-ecological processes unfold within these homes is open and pressing. Especially considering the fact that Global South cities are home to the majority of residents worldwide and if we do not understand how the majority live their intimate daily routines, we cannot aspire to build inclusive, sustainable futures. HOMESCAPES follows water, as it is essential for sustaining everyday life, and goes beyond it into other material and atmospheric components of the home. Stored (stagnant) waters are never only water but are also home to communities of organisms such as bacteria and mosquitoes that eventually continue their lives outside of water. The concept of homescape is proposed to denote a produced place in which interdependent social and ecological processes unfold in and around the domestic, but are not independent of broader socio-economic power relations and ecological dynamics.  Methodologically, this project will not treat southern cities as sources of data, but as sites of theorization in their own right. It combines multi-modal ethnography and water-quality work, approaches that are ground-breaking in building theoretical insights from a diversity of specific urban processes, and contexts.

Mots-clés : global south,urban socio ecological processes,water,air,more than human homes,social power relations
Projet ERC : Astrogeodesy (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : GFZ Helmholtz Centre for Geosciences — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : GFZ
Type d'entité : Recherche
Financement ERC de l'entité : 1498984.0 €

Very Long Baseline Interferometry (VLBI) is a powerful technique in astronomy to generate the most detailed radio images of exotic astronomical objects, mostly Active Galactic Nuclei (AGNs); in geodesy, it enables both societal and scientific applications through its unique and essential role in defining the reference frames that underpin GNSS and its many applications. Some scientific applications of geodesy, such as monitoring sea level rise, require high levels of precision and accuracy. The next generation VLBI system, the VLBI Global Observing System (VGOS), is being developed with the ambitious goal of achieving, on global scales, the accuracy of 1 mm in station position and 0.1 mm/yr in station velocity. For a long time it was thought that the radio propagation medium was the dominant error source and hence considerable effort was invested towards its reduction. However, in more recent years, partly thanks to the pioneering work of the PI, it has become clear that the true potential of geodetic VLBI can never be reached without understanding and correcting for the distortions caused by the angular structure of the AGNs (i.e. distribution of the radio emission on the sky). The Astrogeodesy project will (1) study, characterize, monitor, and interpret the frequency- and time-dependent structure of the AGNs based on VGOS observations and (2) develop approaches to model them as point-like fiducial anchors on the sky. The aim is to close the gap between current capabilities and the target goal of 1 mm accuracy by combining the three disciplines of geodesy, astrometry, and radio astronomy. At the same time, this combination will in return enable VGOS to be a powerful tool providing data to enhance these three fields. About 30 VGOS antennas have been or are being built across the world, and regular VGOS observations are carried out with the completed antennas. It is timely to develop a new data calibration and analysis concept for VGOS through this project.

Mots-clés : very long baseline interferometry,geodesy,terrestrial reference frame,active galactic nuclei
Projet ERC : BOSON (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
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 : 1499129.0 €

Quarkonium, the bound state of a heavy quark pair, is central to many aspects of particle and nuclear physics. Like the hydrogen atom in quantum mechanics, the discovery of the first quarkonium J/psi was the first tangible observation that quarks are physical particles. It provided the first direct evidence of the strong interaction theory in the subatomic world -- quantum chromodynamics (QCD). It is nowadays also understood that quarkonium analogues are important in the new physics search programme at the Large Hadron Collider (LHC) at CERN and in the worldwide dark matter hunt. Quarkonium is also a powerful probe to conduct rich physics studies. Consequently, quarkonium has been measured by almost all experiments. Despite its importance, the quarkonium production mechanism in QCD remains to be understood, which places the theoretical interpretations of quarkonium data on shaky ground. The necessary ingredient to resolve the issues is to radically improve the quality and the precision of theoretical predictions. The primary goals of BOSON are to advance quarkonium studies with three objectives: 1. Pinning down the quarkonium production mechanism; 2. Advancing the precision of theoretical predictions; 3. Extracting maximal physics information from quarkonium data. To achieve them, BOSON will follow three routes: 1) the creation of an automated tool at next-to-leading order for any process involving quarkonia and elementary point particles with interfacing to general-purpose Monte Carlo event generators; 2) next-to-next-to-leading order cross section calculations for inclusive quarkonium processes; 3) phenomenological applications to particle, nuclear, and heavy-ion physics. BOSON outlines a challenging but feasible programme to advance our knowledge of the field, with positive impacts not only on the LHC community, but also on physicists working with facilities like RHIC at BNL, Belle2 at KEK, SPS at CERN and future high-energy experiments (e.g. EIC and FCC).
Projet ERC : FIND (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Human Mobility, Environment, and Space
Entité participante : CMCC Foundation - Euro-Mediterranean Center on Climate Change — Pays : Italie — Rôle : Partner
Acronyme de l'entité : CMCC
Type d'entité : Recherche
Financement ERC de l'entité : 375450.0 €

The FIND project will develop an innovative framework to assess the feasibility and social desirability of limiting global warming through the diffusion of negative emission technologies. Current global climate action is deeply insufficient to deliver the objectives of the Paris Agreement and containing global warming to 1.5 °C will likely require the deployment of carbon dioxide removals. However, the technologies to sequestrate and store carbon from the atmosphere are currently immature, risky, and highly questioned. Understanding the effective diffusion potential of carbon removal methods and their socioeconomic and environmental impacts is pivotal to design future climate action. The FIND project aims to ensure that negative emission technologies act as an enabler, not a barrier, of long-run sustainable development. It brings together different disciplines – namely, climate science, economics, innovation studies, climate finance, integrated assessment, and agent-based modelling - in a coherent and synergic whole. FIND is designed to provide breakthrough evidence about two crucial and under-investigated aspects of carbon removal solutions: (i) how their techno-economic paradigms evolve and relate to the broader technological landscape, and (ii) how immature and uncertain technologies can be financed to provide social value rather than speculative interest. By combing innovation, finance, and political economy into a quantitative theory of carbon removal operationalization unfolding at global scale, FIND will expand the state-of-the-art in climate-energy-economy modelling and reassess decarbonization pathways. The project will evaluate climate and non-climate policies to create robust, no-regret policy portfolios supporting a rapid and sustainable path to a net-zero society. FIND will be of high relevance for public policy and civil society, especially considering Europe’s commitment to reach carbon neutrality by 2050 while spurring green and inclusive growth.

Mots-clés : negative emission technologies sustainable development innovation technological diffusion climate finance integrated assessment modelling
Projet ERC : FoRECAST (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université d'Utrecht — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Automatic Differentiation (AD) systems, like TensorFlow, and probabilistic programming languages (PPLs), like Stan, automate complex computations of derivatives and Bayesian inference tasks. By stream- lining these computations for non-expert users, these high-level systems have accelerated progress across science and society (e.g. by enabling machine learning). Yet, the theoretical foundations needed to build a high-level system for composable programming with derivatives and probabilities are missing. This chasm in our knowledge severely limits the implementation of machine learning techniques, preventing them from reaching their full potential. Specifically, we do not understand (a) how to perform AD on programs built using probabilistic choices and expected values or (b) how to compose (i.e. combine and integrate) Bayesian inference algorithms. FoRECAST addresses this chasm by developing programming language theory and tools for flexible, composable, and efficient calculations with derivatives and prob- abilities. WP 1 develops case studies in collaboration with domain experts, to ensure that FoRECAST creates theory and systems relevant to real-world, complex modelling problems. WP 2 develops the semantic foundations, algorithms, and formalised correctness proofs for composable AD of probabilistic programs. WP 3 builds a practical stochastic (i.e. probabilistic) AD system that synthesises these novel gradient estimation techniques. WP 4 establishes theoretical foundations to compose Bayesian inference algorithms in PPLs. WP 5 implements a user-friendly PPL that facilitates composable Bayesian inference, enabling more flexible modelling for a wider user base. By mathematically formalising, generalising, optimising, and implementing a next generation PPL, this project will lay a trustworthy foundation upon which probabilistic data analysis applications (e.g. reinforcement learning, proteomics modelling, and paleoclimate reconstructions) can rise to the next level.

Mots-clés : semantics,software correctness,probabilistic programming,automatic differentiation
Projet ERC : TOY (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : Université d'Utrecht — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Deep learning (DL) models are encroaching on nearly all our knowledge institutions. Ever more scientific fields—from medical science to fundamental physics—are turning to DL to solve long-standing problems or make new discoveries. At the same time, DL is used across society to inform and provide knowledge. We urgently need to evaluate the potentials and dangers of adopting DL for epistemic purposes, across science and society. This project uncovers the epistemic strengths and limits of DL models that are becoming the single most way we are structuring all our knowledge, and it does so by starting with an innovative hypothesis: that DL models are toy models. A toy model is a type of highly idealized model that greatly distorts the gritty details of the real world. Every scientific domain has their own toy models that are used to "play around" with different features, gaining insight into complex phenomena. Conceptualizing DL models as toy models exposes the epistemic benefits of DL, but also the enormous risk of overreliance. Since toy models are so divorced from the real world, how do we know they are not leading us astray? TOY addresses this fundamental issue. TOY 1) identifies interlocking model puzzles that face DL models and toy models alike, 2) develops a theory of DL (toy) models in science and society based on the function of their idealizations and 3) develops a philosophical theory for evaluating the epistemic value of DL (toy) models across science and society. In so doing, TOY solves existing problems, answers open questions, and identifies new challenges in philosophy of science, on the nature and epistemic value of idealization and toy models; in philosophy of ML, by looking beyond DL opacity and developing a philosophical method for evaluating the epistemic value of DL models; and by bringing siloed debates in ethics of AI together with philosophy of science, providing necessary guidance on the appropriate use and trustworthiness of DL in society.

Mots-clés : machine learning in science,scientific understanding,scientific explanation,idealization,models in science,toy models,values in science,epistemic value
Projet ERC : TRANS-CODE (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Cell Biology, Development, Stem Cells and R egeneration
Entité participante : Université d'Utrecht — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

The translation of mRNAs by ribosomes is a key step in decoding the information stored in our genome. Animal development requires a strict regulation of translation, in particular when transcription is absent, as in most early embryos. A range of mechanisms ensure that mRNAs are translated with the right efficiency and location, in the right cell types and exactly when their protein products are needed. Disruption of this regulation can lead to developmental defects and embryonic lethality. Despite the recognized importance of translation regulation, the impact of translation regulation, and especially localized translation, on protein levels remains largely unknown for most genes. Furthermore, the mechanisms that drive localized and cell-type-specific translation are poorly understood, partly due to a lack of methods that enable the real-time visualization of translation in live embryos. The goal of this proposal is to discover translationally regulated mRNAs across the genome in early development, and reveal, with single-molecule precision, how spatiotemporal cues and cell type-specific mechanisms drive differential protein translation. Using ribosome profiling, we will create a genome-wide single-cell map of translation efficiencies during embryonic development of C. elegans, thus delineating the translation landscape that guides development. Using real-time single-molecule translation imaging, we will reveal how local translation patterns are formed and maintained between and within cells. Finally, we will explore how RNA-binding proteins modulate both translation efficiencies and spatial organization, to reveal the underlying mechanisms that drive translation during development. This combination of genome-wide and single-molecule studies will lay the groundwork for understanding how spatial cues and cell-type-specific mechanisms drive precise protein expression, which ultimately shapes cellular identity in early development.

Mots-clés : translation regulation,development,c elegans,single molecule imaging,ribosome profiling,rna binding proteins
Projet ERC : Immuno-SBC (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Princess Máxima Center — Pays : Pays-Bas — Rôle : Partner
Type d'entité : Autres
Financement ERC de l'entité : 163232.0 €

Approximately 1 in 5 newly diagnosed cancers is a second or subsequent cancer related to treatment for a first cancer. Second breast cancers (SBCs) are the most commonly diagnosed. Those who develop SBCs have reduced treatment options and worse outcomes than comparable individuals with first primary breast cancers. There are over 12 million female cancer survivors in the EU, of whom at least 15% will develop an SBC. A better understanding of the etiology and risk factors for SBC is therefore essential. There is an intriguing and poorly understood negative association between systemic autoimmune diseases and breast cancer, repeatedly documented in distinct populations. My preliminary data further suggests that systemic autoimmune disease interacts with chemotherapy receipt to modify the risk of SBCs. However, no research groups have interrogated the interaction among autoimmunity, cancer treatment, and SBC risk. I propose to address this gap by bringing together population-based studies, multi-omic tools, and innovative statistical modelling. I have proposed three complementary Scientific Aims to understand the epidemiological and biological relevance of autoimmune disease in SBC. In Aim 1, I will use a novel approach to link large cohorts of cancer survivors with medical data to capture the course of autoimmune disease after cancer and its relationship with SBC risk. In Aim 2, I will use germline genotyping data to define "autoimmune states" reflecting the true range of sub-clinical autoimmune phenotypes. In Aim 3, I will test the association between autoimmune state and SBC risk, and the interaction with chemotherapy. This project thus introduces a novel paradigm for understanding of the etiology of treatment-associated cancers. Given the fundamental importance of immune state in cancer outcomes, and the number of people at risk of SBC, this project will have a profound impact on cancer survivorship research.

Mots-clés : breast cancer autoimmunity chemotherapy radiotherapy genetics statistical modelling late effects cancer survivorship