Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SPINRG (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : University of Cambridge — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1250043.0 €

The objective of this proposal is to develop effective methods for the analysis of classical continuous spin systems, with focus on their stochastic dynamics and on spin systems with hyperbolic symmetry. The latter are related to reinforced random walks and to random operators. In particular, I propose to develop mathematical methods for renormalisation group analysis of such systems. Renormalisation is a central concept in theoretical physics, explaining a vast range of phenomena heuristically. While its rigorous implementation is difficult, when a renormalisation group approach to a problem is available, it provides very detailed control and also explains universality. Both, in stochastic dynamics of large scale systems and in random matrix theory, great progress has been achieved recently. In stochastic dynamics, this applies in particular to the problem of existence of solutions to SPDEs and their regularity (ultraviolet problem). This proposal focuses on the complementary regime of long time asymptotics (infrared problem), where important results have been obtained via exact solutions but robust methods remain scarce. In random matrix theory, very general classes of random matrices have been understood, yet those with finite dimensional structure like the Anderson model remain out of reach. Spin systems with hyperbolic symmetry and supersymmetry arise in the descriptions of such random matrices, and their simplified versions are prototypes for the understanding of the original models. They also describe linearly reinforced random walks which are of independent interest, and allow for some of the quantum phenomena to be reinterpreted probabilistically. I will build on methods that I developed in previous work, including renormalisation group analysis for static systems, the development of a renormalisation group approach to Glauber dynamics, the study of spin systems with hyperbolic symmetry and supersymmetry, and my experience in random matrix theory.

Mots-clés : renormalisation group,spin systems,glauber dynamics,random matrices
Projet ERC : BPI (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1662942.0 €

The objective of this research agenda is to provide a new framework to model and analyze dynamics of group beliefs, in order to study phenomena such as group polarization, segregation and inter-group discrimination. We introduce a simple new heuristic, the Bayesian Peer Influence heuristic (BPI), which is based on rational foundations and captures how individuals are influenced by others' beliefs. We will explore the theoretical properties of this heuristic, and apply the model to analyze the implications of belief dynamics on social interactions. Understanding the formation and evolution of beliefs in groups is an important aspect of many economic applications, such as labour market discrimination. The beliefs that different groups of people have about members of other groups should be central to any theory or empirical investigation of this topic. At the same time, economic models of segregation and discrimination typically do not focus on the evolution and dynamics of group beliefs that allow for such phenomena. There is therefore a need for new tools of analysis for incorporating the dynamics of group beliefs; this is particularly important in order to understand the full implications of policy interventions which often intend to "educate the public''. The BPI fills this gap in the literature by offering a tractable and natural heuristic for group communication. Our aim is to study the theoretical properties of the BPI, as well as its applications to the dynamics of group behavior. Our plan is to: (i) Analyze rational learning from others’ beliefs and characterise the BPI. (ii) Use the BPI to account for cognitive biases in information processing. (iii) Use the BPI to analyze the diffusion of beliefs in social networks. (iv) Apply the BPI to understand the relation between belief polarization, segregation in education and labour market discrimination. (v) Apply the BPI to understand the relation between belief polarization and political outcomes.

Mots-clés : group beliefs,peer influence,belief polarization,segregation,discrimination,group dynamics,bayesian learning,political polarization,information diffusion
Projet ERC : GemX (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3355460.0 €

The observation that matter dominates over anti-matter in the Universe is one of the most critical open questions in physics. A natural explanation of this asymmetry postulates neutrinos as their own anti-particles, usually referred to as Majorana particles. The only practical way to establish the Majorana character of neutrinos is the experimental search for neutrinoless double-beta decay (NDBD). This decay violates lepton-number conservation and would establish new physics beyond the Standard Model of particle physics. The Germanium eXploration (GemX) project will focus on cutting-edge research towards a ton-scale NDBD decay experiment based on germanium detectors enriched in 76Ge, and thereby sustain a European leadership also in the next-generation worldwide experimental competition. With its superior energy resolution and lowest background, a one-ton 76Ge experiment has potentially the highest sensitivity for discovering NDBD decay amongst the next-generation experiments. A discovery would be groundbreaking in the fields of particle physics, astrophysics and cosmology. The goal of GemX is to develop and evaluate novel HPGe detectors enriched in 76Ge, test their performance in LEGEND-200 and inform the design decisions of the future flagship 1000-kg experiment LEGEND-1000, which the PI leads as elected European spokesperson. GemX will (1) investigate new Ge detector designs with increased mass and improved pulse shape discrimination to enhance background reduction; (2) develop a crystal growth process from germanium material enriched in 76Ge for large high-purity Ge crystals with suitable net-impurity concentrations in Europe; (3) develop the production of large Ge detectors enriched in 76Ge with minimal activation by cosmic radiation and with full control of surface contaminations from alpha contaminations; (4) deploy, test and operate the novel detectors in the TUM underground liquid argon test stand and in LEGEND-200 at the LNGS, Italy.

Mots-clés : neutrino,astroparticle physics
Projet ERC : MicroC (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1540347.5 €

The occurrence of therapeutic resistance is a major cause for the small effect on overall survival showed by targeted cancer therapies. Whilst experimental strategies to evaluate available treatments have been faced by an ever increasing number of possible combinations, computational approaches have been challenged by the lack of a framework able to model the multiple interactions encompassed by the three major factors affecting therapeutic resistance: selection of resistant clones, adaptability of gene signalling networks, and a protective and hypoxic tumour microenvironment. Here I propose a novel modelling framework, Agent-Based Modelling of Gene Networks, which brings together powerful computational modelling techniques and gene networks. This combination allows biological hypotheses to be tested in a controlled stepwise fashion, and it lends itself naturally to model a heterogeneous population of cells acting and evolving in a dynamic microenvironment, which is needed to predict therapeutic resistance and guide effective treatment selection. Using triple negative breast cancer (TNBC) as a testing case (15% of breast cancers, lacks validated), I propose to: 1. Develop a computational model of the TNBC tumour microenvironment using in-vitro and in-vivo, including patient-derived, models and data from clinical samples. 2. Validate the ability of the model to predict driver genes conferring a survival advantage to cancer cells in a hypoxic microenvironment. 3. Predict combinations of druggable targets to tackle TNBC therapeutic resistance. 4. Select most effective drug combinations and validate pre-clinically. This project will deliver pre-clinically validated drug combinations, new therapeutic targets and a virtual environment to study individual tumours and predict therapeutic resistance. Complementing and empowering experimental models and assays, microC will offer a new powerful tool for diagnosis and therapy.
Projet ERC : FEAST (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Ghent University — Pays : Belgique — Rôle : PI
Acronyme de l'entité : UGent
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

The ongoing industrial revolution is the driver of a rapidly advancing shift in the division of labour between humans on the one hand and machines and algorithms on the other. This is the cause of significant challenges in the job market, such as the emergence of important skills gaps that need to be addressed by extensive upskilling or reschooling of workers. This requires considerable forethought and hence insight into the future job markets, as well as an understanding of how to best meet the job market's current and future needs. Substantial value is to be gained at all levels: from individual workers, over talent and human resources management within companies, to the determination of policy at governmental level. This Proof of Concept proposal will address these challenges by leveraging results from the ERC Consolidator Grant FORSIED which lend themselves well to a uniquely suited and elegant data-driven approach. In particular, the method Conditional Network Embedding (CNE) offers a powerful framework for making sense of the diverse information relevant to human talent and the job market. It provides a platform to tackle a diverse range of use cases in a uniform manner. Moreover, a distinguishing advantage of CNE is that it offers mechanisms for compensating for existing biases in the job market, ensuring fairness, non-discrimination, and inclusion when deployed to these use cases. During the project, a prototype platform will be developed, in tight collaboration with actors in the private and public sectors. This prototype will be evaluated, the IPR position investigated, and a market study conducted leading to a road to market strategy.

Mots-clés : data science,network embedding,fairness in data science,human resources,talent managment,labour,market,conditional network embedding,recommender systems
Projet ERC : exoZoo (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : Partner
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 113641.61 €

The ongoing search for a second Earth has revealed an astounding diversity in the population of planets orbiting other stars. This eclectic zoo of other worlds shows little similarity with our own solar system. The key to understanding this diversity lies in exoplanet atmospheres, which hold vital information on their formation histories and evolutionary pathways. To access them, I propose three ambitious new windows into exoplanet characterization that will: i) Deliver the largest homogenous study of exoplanet atmospheres at high spectral resolution, and provide a novel framework that combines multi-resolution data to deliver precise atmospheric measurements. This will place unprecedented constraints on the physical causes of exoplanet diversity and is a game changer in understanding their origins. ii) Perform the first robust study of the reflective properties of exoplanet atmospheres at high spectral resolution, constraining their evolution and demonstrating how to interpret, and crucially, optimise high-resolution observations for the upcoming biomarker hunt with the extremely large telescopes. This may be our only way to characterize the nearest habitable worlds. iii) Pioneer an innovative photometric monitoring technique for exoplanet atmospheres and use it to measure their rotation, detect giant storms, and hunt for occulting moons to begin surveying their demographics. The achievement of these three main objectives will be a ground-breaking step forward in our understanding of exoplanets and Earth’s place amongst them, bringing us ever closer to answering the question: are we alone?

Mots-clés : exoplanet atmospheres
Projet ERC : Lost Frontiers (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Wales Trinity Saint David — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : UWTSD
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 17835.0 €

The only lands on Earth that have not been explored in any depth by science are those that have been lost to the oceans. Global warming at the end of the last Ice Age led to the inundation of vast landscapes that had once been home to thousands of people. These lost lands hold a unique and largely unexplored record of settlement and colonisation linked to climate change over millennia. Amongst the most significant is Doggerland. Occupying much of the North Sea basin between continental Europe and Britain it would have been a heartland of human occupation and central to the process of re-settlement and colonisation of north Western Europe during the Mesolithic and the Neolithic. Within this submerged landscape lies fragmentary yet valuable evidence for the lifestyles of its inhabitants including the changes resulting from both the encroaching sea and the introduction of Neolithic technologies. This inundated landscape cannot be explored conventionally, however pioneering work by the applicant’s research group has led to the rediscovery of Doggerland through the creation of the first detailed topographic maps relating to human occupation in the Early Holocene. Within this project world-leading innovators in the fields of archaeo-geophysics, molecular biology and computer simulation will develop a ground-breaking new paradigm for the study of past environments, ecological change and the transition between hunter gathering societies and farming in north west Europe. It will: 1) use the latest seismic reflectance data available to generate topographical maps of the whole of early Holocene Doggerland that are as accurate and complete as possible. 2) reconstruct and simulate the palaeo-environments of Doggerland using ancient DNA extracted directly from sediment cores. 3) explore the Mesolithic landscapes and also identify incipient Neolithic signals indicating early contact and development within the region of Doggerland.

Mots-clés : marine archaeology,palaeolandscapes,coastal shelf prehistoric research
Projet ERC : Tetrapod Origin (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Uppsala University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2450143.0 €

The origin of tetrapods (land vertebrates) during the Devonian period, a key event for the terrestrial ecosystem, is illuminated by splendid fossil discoveries but very ill-served by the dominant theoretical framework. This framework has two weaknesses: the persistence of a simplistic evolutionary scenario that has already been falsified, and a failure to properly consider the place of tetrapods in the developing terrestrial ecosystem. The scenario envisages tetrapods evolving from ‘elpistostegids’ like Tiktaalik in an aquatic environment during the Late Devonian, but fails to account for the existence of tetrapod trackways that are older than the elpistostegids, and cannot explain the evolution of structures such as a sacrum (link between pelvis and vertebral column) that lack inherent value for aquatic locomotion. The extraordinary value of the trackways as behavioural records of living animals is ignored. Environmental contexts like ‘flooded forests’ are proposed for the evolution of tetrapods without analysis of the environments where their tracks are preserved. Unless this situation is remedied the subject cannot progress. To solve these problems, I will combine my world-leading expertise on Devonian tetrapods with the skills of a team of world-class experts on trace fossils, morphometrics, geochemistry, sedimentology, Devonian land plants, and synchrotron tomography. This approach is unprecedented in the study of the origin of tetrapods. We will undertake a bold fieldwork program, coupled with cutting-edge, high-precision, multidisciplinary analysis, which will power the first-ever analysis of the fish-tetrapod transition in a fully elaborated environmental and ecological context. This will at last allow us to fully integrate tetrapods into the vibrant research area of terrestrial ecosystem evolution. We will also search systematically for the still-missing holy grail of early tetrapod research: body fossils contemporary with the earliest tetrapod trackways.

Mots-clés : ecosystem reconstruction
Projet ERC : CosmoChart (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Sorbonne Université — Pays : France — Rôle : PI
Acronyme de l'entité : Sorbonne U
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998437.0 €

The origin of the matter-antimatter asymmetry of the universe and the nature of dark matter are among the most fundamental and challenging questions in physics. Their undeniable importance has placed them in the forefront of the experimental and theoretical research in particle physics, cosmology and astrophysics. Our experimental probes are now at the outset of exploring the multi-TeV energy scale. To fully exploit the experimental effort, to design effective search strategies and correctly interpret the experimental results, we must develop reliable theoretical understanding of the plausible dynamics at this scale. The TeV scale is a new threshold. In this regime, the interactions hypothesised in a variety of well-motivated theories manifest as long-range. This is true for the most widely studied particle-physics scenario for dark matter, particles coupled to the Weak interactions of the Standard Model, as well as many other models. Moreover, many theories of matter-antimatter asymmetry generation invoke heavy particles that couple to lighter force mediators. Long-range interactions imply very different dynamics than the contact-type interactions most commonly considered in the past. They give rise to non-perturbative effects, with the most prominent being the existence of bound states. Such effects can change the experimental signatures very significantly. CosmoChart will comprehensively investigate the implications of long-range interactions along two directions: I. The dark matter thermal decoupling in the early universe and indirect detection. II. The particle-antiparticle asymmetry generation and washout. The results will have implications for most experimental probes. As the long-range dynamics becomes increasingly more important at higher scales, the investigations of CosmoChart will chart particle cosmology at the TeV scale and beyond.

Mots-clés : dark matter,matter antimatter asymmetry,bound states,long range interactions
Projet ERC : ORACLE (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Erasmus MC — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1495715.0 €

The origins of Alzheimer’s disease (AD) remain elusive. The long pre-clinical phase of AD is universally recognized, but it is not known when predisposition for AD develops nor when the first signs and symptoms become discernable. In this regard, an essential role is played by the ‘reserve’ capacity of the brain, which is built up in early life and acts as buffer against adverse risk factors later in life. However, life-time trajectories of build up and loss of reserve and its determinants remain poorly understood. In ORACLE, I aim to unravel the origins of AD by studying reserve across the entire life-span: from in utero to end of life. The underlying hypothesis is that etiologic factors exert their effect on the risk of AD during the entire life-span, through build-up and loss of reserve. Such life-course approach to study reserve is worldwide unique and constitutes truly ground-breaking research aimed at unraveling the earliest origins of AD. Key objectives are: 1) To study trajectories of reserve across the entire lifespan. 2) To study factors that shape reserve in early life. 3) To study factors that determine onset and early loss of reserve. I will compile a life-course cohort that consists of three population-based samples totalling 40,829 persons that together cover the entire life-span: children in Generation R Study (in utero – 18 yrs); parents in Generation R Study (18–45 yrs); and the Rotterdam Study (45 yrs – death). Reserve will be quantified structurally using imaging techniques that measure volumetry, perfusion and connectivity as well as functionally by measuring cognitive and non-cognitive brain functions. I will study genetic and non-genetic risk factors of AD and their effects on reserve. Results from ORACLE will provide ground-breaking new insights into the earliest origins of AD. In turn, these insights are of major importance to enable the early identification of persons at highest risk of AD and develop targeted prevention for these persons.

Mots-clés : life course,population based,cohort studies,alzheimer s disease,cognitive reserve,brain reserve,imaging,genetics