Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : BICAEHFID (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : Spanish National Research Council — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CSIC
Type d'entité : Recherche
Financement ERC de l'entité : 2220396.0 €

Our understanding of the emergence and dispersal of the earliest tool-making hominins has been revolutionised in the last decade, with sites in eastern Africa and China pushing both events more than half a million years earlier than previously thought. Traditional models linking biological speciation, cultural innovation and migration events with climatic pulses have remained theoretical, and recent discoveries suggest that the picture of the earliest human colonization across the Old World is far more complex, demanding heuristic approaches to understand the biogeography and adaptive behaviours of early humans. This project will be the first substantive attempt to produce a global synthesis of earliest human occupation dynamics by comparing the world’s longest sequences of early archaeological sites, namely eastern Africa and China. Our objective is to understand the alternative evolutionary trajectories adopted by hominins that shared an overarching biological and cultural background, but who faced different climatic and biogeographic challenges and opportunities. The ambition of our global-scale objectives is accompanied by the unmatched quality of our datasets and the ground-breaking perspective we will adopt in their study. Fieldwork in the two most renowned sequences in each region alongside a primary study of additional top-quality assemblages in both subcontinents, will be combined with extensive metadata sets to produce comprehensive views of temporal trends and paleoecological patterns. Our state-of-the-art methodological sets (which combine an exceptionally diverse range of disciplines from geochemistry to niche modelling) and ground-breaking analytical perspective (which considers data from micro-stratigraphy to satellite imaging) will enable us to develop new approaches to challenge established paradigms and produce a new picture of the biogeographic adaptations of early stone-tool makers.

Mots-clés : palaeolithic archaeology,early stone age,human evolution
Projet ERC : NPTEV-TQP2020 (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : National Institute for Nuclear Physics — Pays : Italie — Rôle : Partner
Acronyme de l'entité : INFN
Type d'entité : Recherche
Financement ERC de l'entité : 228154.61 €

Our understanding of the subatomic world and of the very fabric of the space-time is encompassed in a theory which is the result of all past experimental observations and theoretical developments: the Standard Model of Particle Physics. Yet cosmological observations and theoretical arguments lead us to conclude that new phenomenology, new particles, forces, or a new space-time structure is waiting to be uncovered. Naturalness of the recently discovered Higgs boson suggests that new phenomena should appear at the tera-electronvolt (TeV) scale, and will be accompanied by modifications to the dynamics of the heaviest elementary particle known: the top quark. The aim of this proposal is to perform five measurements involving top quarks with the data that will be collected by the ATLAS experiment at the upcoming Run II (2015-18) of the Large Hadron Collider (LHC): the top quark mass, the CP violation in B hadron decays from the top, the top-Z boson couplings, the search for the top's Flavour Changing Neutral decays, and the search for heavy resonances decaying to top pairs. While measuring these properties is nothing new, the measurements are performed coherently using novel techniques beyond state-of-the-art to push the boundaries on the sensitivity of the limited Run II data, hence allowing the discovery of new phenomena at the LHC before 2020.

Mots-clés : atlas,top physics
Projet ERC : ChiCC (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Liverpool — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999890.0 €

Over 60% of the world’s top selling small molecule drug compounds are chiral and, of these, approximately 80% are marketed as single enantiomers. Surprisingly, and despite the tremendous advances made in catalysis over the past several decades, the average “chiral complexity” of drug discovery libraries has actually decreased, while, at the same time the “chiral complexity” of marketed drugs has increased. Consequently, there is now an urgent need to provide efficient processes that access directly privileged chiral “3D” building blocks. It is our philosophy that catalysis holds the key here and new processes should be based upon atom and step economical platforms that exert control over both absolute and relative stereochemistry. Palladium catalysed cross-coupling reactions of aryl (pseudo)halides with organo-nucleophiles (esp. the Suzuki coupling) have become mainstays of the pharmaceutical industry. Here, multiple “concession” steps are usually required to prepare the reaction partners, thereby detracting from atom and step economy. Further, these processes predominantly provide planar “2D” structures and are not well suited to the production of chiral “3D” building blocks. Consequently, methods that allow feedstock precursors (e.g. alkenes and aryl C-H bonds) to be combined directly in enantioselective or enantiospecific C-C bond formations are highly desirable. Cross-couplings of this type would circumvent “concession” steps, thereby minimising cost, effort and waste; however, such processes are highly challenging because of issues associated with regio- and stereocontrol. Recently, we developed prototype catalyst systems that can address this. In the proposed ERC project, these exciting preliminary results will be developed into a wider family of processes where asymmetric C-C bond formations are achieved directly by C-H activation. The new methods, which fulfil modern reaction ideals of atom and step economy, will likely find broad use in applied settings.

Mots-clés : synthetic methodology,cross coupling,enantioselective,catalysis,atom and step economy
Projet ERC : NOMLI (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
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 : 2292068.0 €

Over a decade, the field of optomechanics has progressed to the point of enabling first quantum experiments on mesoscopic mechanical devices. This maturity culminates with nanoscale semiconductor systems, which operate at very high mechanical frequency and allow intense interaction between light and mechanical motion. On top of representing a new class of elementary quantum systems, nano-optomechanical devices can sense forces at small scale with high speed and resolution, down to the quantum limit. They could probe physical interactions in complex environments, like liquids, with a unique degree of control, and thus bring new science and applications. NOMLI explores original physics at the interface of nano-optomechanics and liquids, be they classical or quantum. A first objective is to realize nano-optomechanical rheological measurements at very high frequency (GHz) and small scale (μm) in classical liquids, and investigate the solid-like behavior of liquids in previously inaccessible regimes. A second objective is to optically cool a nano-optomechanical resonator immersed in a classical liquid down to the quantum regime, and analyze mechanical decoherence in such complex environment. As third objective, a quantum liquid of light will be artificially created in a set of nonlinear photonic resonators. Its viscous force will be investigated nano-optomechanically, and monitored as the liquid undergoes the superfluid transition. Finally a new type of quantum liquid, fully optomechanical in nature, will be formed in an ensemble of resonators at ultra-low temperature. Viscosity, dynamics and superfluidity of this new phase of light and matter will be investigated, using engineered photon-photon interactions mediated by mechanical motion. NOMLI will build a detailed picture of physical mechanisms at play, at the quantum level and at small scale, when a miniature mechanical force probe evolves in a liquid, where chemical and biological processes usually take place.
Projet ERC : TUgbOAT (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Warsaw — Pays : Pologne — Rôle : PI
Acronyme de l'entité : UW
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1510800.0 €

Over last 50 years, extensive algorithmic research gave rise to a plethora of fundamental results. These results equipped us with increasingly better solutions to a number of core problems. However, many of these solutions are incomparable. The main reason for that is the fact that many cutting-edge algorithmic results are very specialized in their applicability. Often, they are limited to particular parameter range or require different assumptions. A natural question arises: is it possible to get “one to rule them all” algorithm for some core problems such as matchings and maximum flow? In other words, can we unify our algorithms? That is, can we develop an algorithmic framework that enables us to combine a number of existing, only “conditionally” optimal, algorithms into a single all-around optimal solution? Such results would unify the landscape of algorithmic theory but would also greatly enhance the impact of these cutting-edge developments on the real world. After all, algorithms and data structures are the basic building blocks of every computer program. However, currently using cutting-edge algorithms in an optimal way requires extensive expertise and thorough understanding of both the underlying implementation and the characteristics of the input data. Hence, the need for such unified solutions seems to be critical from both theoretical and practical perspective. However, obtaining such algorithmic unification poses serious theoretical challenges. We believe that some of the recent advances in algorithms provide us with an opportunity to make serious progress towards solving these challenges in the context of several fundamental algorithmic problems. This project should be seen as the start of such a systematic study of unification of algorithmic tools with the aim to remove the need to “under the hood” while still guaranteeing an optimal performance independently of the particular usage case.

Mots-clés : online algorithms,matchings and allocations,stochastic algorithms,worst case analysis
Projet ERC : DeAge (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University of Oviedo — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2456250.0 €

Over many years, our research group has explored the complex relationship between cancer and ageing. As part of this work, we have generated mouse models of protease deficiency which are protected from cancer but exhibit accelerated ageing. Further studies with these mice have allowed us to unveil novel mechanisms of both normal and pathological ageing, to discover two new human progeroid syndromes, and to develop therapies for the Hutchinson-Gilford progeria syndrome, now in clinical trials. We have also integrated data from many laboratories to first define The hallmarks of ageing and the current possibilities for Metabolic control of longevity. Now, we propose to leverage our extensive experience in this field to further explore the relative relevance of cell-intrinsic and -extrinsic mechanisms of ageing. Our central hypothesis is that ageing derives from the combination of both systemic and cell-autonomous deficiencies which lead to the characteristic loss of fitness associated with this process. Accordingly, it is necessary to integrate multiple approaches to understand the mechanisms underlying ageing. This integrative and multidisciplinary project is organized around three major aims: 1) to characterize critical cell-intrinsic alterations which drive ageing; 2) to investigate ageing as a systemic process; and 3) to design intervention strategies aimed at expanding longevity. To fully address these objectives, we will use both hypothesis-driven and unbiased approaches, including next-generation sequencing, genome editing, and cell reprogramming. We will also perform in vivo experiments with mouse models of premature ageing, genomic and metagenomic studies with short- and long-lived organisms, and functional analyses with human samples from both progeria patients and centenarians. The information derived from this project will provide new insights into the molecular mechanisms of ageing and may lead to discover new opportunities to extend human healthspan.

Mots-clés : longevity,progeria,proteostasis,proteases,senescence
Projet ERC : ENHANCEDQMMR (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Bremen — Pays : Allemagne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 185312.5 €

Over the last 20 years, qualitative methods in political science have developed rapidly on three dimen-sions. First, set theory was formulated as an alternative to what is called the quantitative worldview. Second, process tracing for the analysis of mechanisms evolved as a complement to the estimation of marginal effects. Process tracing has also been tied to Bayesianism as opposed to frequentism. Third, process tracing became an element of multi-method research (MMR), integrating it with frequentist statistics or Qualitative Comparative Analysis (QCA). An important element of the development of qualitative methods is its contrast with quantitative methods. At the same time, quantitative researchers critically commented on that development. The constant exchange has contributed to the progress of qualitative methods, but the debate has reached an impasse in some respects, or has pursued one line of development while neglecting others. Building on state-of-the-art qualitative methods, ENHANCEDQMMR seeks to overcome this impasse and to explore new ground.It makes four significant contributions to the progress of standalone qualitative methods and as part of MMR. First, it examines experimentally how researchers decide between a set-relational and correlational view on causation and whether they can realize designs in accord with their initial decision. Second, it develops tools for sensitivity analyses, diagnostics, and the modeling of diverse data structures via QCA for strengthening QCA-based inference. Third, it com-pares the performance of QCA and regression analyses under simulated data-generating processes with the goal of generating comparative diagnostics, possibly allowing one to adjudicate between both methods in observational research. Fourth, it formulates standards for Bayesian MMR by combining Bayesian process tracing with Bayesian statistics and Bayesian QCA, respectively. The insights of the project will be implemented in freely available software.

Mots-clés : alphabetically  case studies,causal inference,multi method designs,nested analysis,political science methods,process tracing,qualitative comparative analysis  qca,research design,set theory
Projet ERC : PALAEOFARM (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : Ludwig-Maximilians-Universität München — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 989253.75 €

Over the last 50 years, chicken production has increased fivefold, chicken growth rate has tripled, and milk production per cow has doubled. Yet, many of the biotechnological tools responsible for this accelerated trend are now under threat of becoming obsolete. While the causes are numerous, one significant driver is a dramatic reduction of genetic diversity in livestock populations. Cycles of agricultural productivity growth and decline have occurred throughout European history, spurred by major historical forces such as the spread of empires and continent-wide epidemics. For example, productivity crashed between the 4th-13th centuries, only to rebound during the Agricultural Revolution of the 13-18th centuries. Fluctuating levels of genetic diversity were likely both cause and remedy to these cycles. Genetic diversity acts as a fuel for selection: the lower it is, the more difficult it is to improve traits, and the more likely that epidemics will develop and spread. Given this importance, maintaining diversity amongst livestock is recognised as one of the UN’s Sustainable Development Goals. Despite this, we lack any understanding of how much genetic variability was present, and subsequently lost, before, during, and after either the Green or Agricultural Revolutions, nor do we understand how efficiently it was utilised. PALAEOFARM will assess the long-term sustainability of modern breeding practices by unravelling how genetic variability was leveraged across major agricultural transitions in European history. Using an innovative combination of ancient DNA, archaeozoology, and experimental immunology, I will explore how livestock populations withstood epidemics and selective breeding in a world without antibiotics or quantitative genetic techniques. This will provide a novel perspective on how a multi-billion euro industry, responsible for feeding billions of people, can be sustained in the face of major biotechnological obsolescence.

Mots-clés : livestock genomics,population genomics,ancient dna,immunology
Projet ERC : CLaSS (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Tübingen — Pays : Allemagne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 258150.0 €

Over the last 8000 years, the Fertile Crescent of the Near East has seen the emergence of cities, states and empires. Climate fluctuations are generally considered to be a significant factor in these changes because in pre-industrial societies they directly relate to food production and security. In the short term, ‘collapse’ events brought about by extreme weather changes such as droughts have been blamed for declines in population, social complexity and political systems. More broadly, the relationships between environment, settlement and surplus drive most models for the development of urbanism and hierarchical political systems. Studies seeking to correlate social and climatic changes in the past tend either to focus on highly localised analyses of specific sites and surveys or to take a more synthetic overview at much larger, even continental, scales. The CLaSS project will take a ground breaking hybrid approach using archaeological data science (or ‘big data’) to construct detailed, empirical datasets at unprecedented scales. Archaeological settlement data and archaeobotanical data (plant and tree remains) will be collated for the entire Fertile Crescent and combined with climate simulations derived from General Circulation Models using cutting edge techniques. The resulting datasets will represent the largest of their kind ever compiled, covering the period between 8000BP and 2000BP and an area of 600,000km2. Collecting data at this scale will enable us to compare population densities and distribution, subsistence practices and landscape management strategies to investigate the question: What factors have allowed for the differential persistence of societies in the face of changing climatic and environmental conditions? This ambitious project will provide insights into the sustainability and resilience of societies through both abrupt and longer term climate changes, leveraging the deep time perspective only available to archaeology.

Mots-clés : social complexity,archaeological data science,urbanism,geographical information systems
Projet ERC : CLaSS (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : Durham University — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1100105.0 €

Over the last 8000 years, the Fertile Crescent of the Near East has seen the emergence of cities, states and empires. Climate fluctuations are generally considered to be a significant factor in these changes because in pre-industrial societies they directly relate to food production and security. In the short term, ‘collapse’ events brought about by extreme weather changes such as droughts have been blamed for declines in population, social complexity and political systems. More broadly, the relationships between environment, settlement and surplus drive most models for the development of urbanism and hierarchical political systems. Studies seeking to correlate social and climatic changes in the past tend either to focus on highly localised analyses of specific sites and surveys or to take a more synthetic overview at much larger, even continental, scales. The CLaSS project will take a ground breaking hybrid approach using archaeological data science (or ‘big data’) to construct detailed, empirical datasets at unprecedented scales. Archaeological settlement data and archaeobotanical data (plant and tree remains) will be collated for the entire Fertile Crescent and combined with climate simulations derived from General Circulation Models using cutting edge techniques. The resulting datasets will represent the largest of their kind ever compiled, covering the period between 8000BP and 2000BP and an area of 600,000km2. Collecting data at this scale will enable us to compare population densities and distribution, subsistence practices and landscape management strategies to investigate the question: What factors have allowed for the differential persistence of societies in the face of changing climatic and environmental conditions? This ambitious project will provide insights into the sustainability and resilience of societies through both abrupt and longer term climate changes, leveraging the deep time perspective only available to archaeology.

Mots-clés : social complexity,archaeological data science,urbanism,geographical information systems