Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DoMInIon (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Universität Innsbruck — Pays : Autriche — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2488703.0 €

Being able to clarify the atomistic dynamics of molecular collisions and chemical reactions has been a central research goal for decades. For reactions of charged particles in particular, the importance of quantum dynamics is barely understood, as quantum state-resolved experiments beyond total cross section measurement are very challenging and most theoretical descriptions still rely on quasi-classical approaches. In particular, quantum scattering resonances, known by now to be relevant in a few well-studied neutral molecule reactions, have never been observed for ion-molecule collisions up to now. In the past years we have spearheaded research on crossed-beam reactive scattering of ions with neutral molecules. Our measured differential scattering cross sections could provide detailed insight into the dynamics of polyatomic reactions and allowed us to discover several new reaction mechanisms. In this project, we propose a novel experimental approach to achieve a multifold improved resolution for the scattering images, which will allow us to answer several key questions: Which product quantum states are populated in molecular ions that are produced in three- and four-atom reactions? How do quantum scattering resonances influence the collision dynamics and the product state distribution? Which momentum vector correlations govern the three-body break-up in ion-neutral reactions and which transition states are responsible for these dynamics? How are ionic reactions contributing to the radiation damage of biological molecules in cells? Our proposed experimental approach can answer these questions and will thereby reach a new domain for the investigation of ion-molecule reactions with unprecedented quantum state control for three- and four-atom reactions and highly differential insight into polyatomic reactions.

Mots-clés : molecular collisions,ion molecule reactions,reaction dynamics,ion imaging,quantum scattering,photoionization
Projet ERC : BSP (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : Tilburg University — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TiU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1496944.0 €

Belief systems research is vital for understanding democratic politics, extremism, and political decision-making. What is the basic structure of belief systems? Clear answers to this fundamental question are not forthcoming. This is due to flaws in the conceptualization of belief systems. The state-of-the-art treats a belief system as a theoretical latent variable that causes people’s responses on attitudes and values relevant to the belief system. This approach cannot assess a belief system because it cannot assess the network of connections between the beliefs–attitudes and values–that make up the system; it collapses across them and the interrelationships are lost. The Belief Systems Project conceptualizations belief systems as systems of interconnecting attitudes and values. I conceptualize attitudes and values as interactive nodes in a network that are analysed with network analyses. With these conceptual and empirical tools, I can understand the structure and dynamics of the belief system and will be able to avoid theoretical pitfalls common in belief system assessments. This project will move belief systems research beyond the state-of-the-art in four ways by: 1. Mapping the structure of systems of attitudes and values, something that is not possible using current methods. 2. Answering classic questions about central concepts and clustering of belief systems. 3. Modeling within-person belief systems and their variations, so that I can make accurate predictions about partisan motivated reasoning. 4. Testing how external and internal pressures (e.g., feelings of threat) change the underlying structure and dynamics of belief systems. Using survey data from around the world, longitudinal panel studies, intensive longitudinal designs, experiments, and text analyses, I will triangulate on the structure of political belief systems over time, between countries, and within individuals.

Mots-clés : political psychology,social psychology,ideology,belief systems,network psychometrics
Projet ERC : SystemShift (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Humboldt-Universität zu Berlin — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999125.0 €

Biodiversity loss is a global crisis threatening human wellbeing, and the main driver is how we use land. Decisions about land use are made in social-ecological systems, yet conservation science is currently ill-equipped to consider the complex and dynamic interactions between land-use actors and their environment. This translates into conservation failures and missed opportunities. My overarching goal is to develop new, interdisciplinary concepts and approaches that enable a different, social-ecological perspective on land use in conservation. This promises major breakthroughs in our understanding of threats to biodiversity and how to design effective conservation strategies. My project will be organized in three main steps. STEP 1 will develop novel concepts to identify key combinations of land-use actors, practices, and threats to biodiversity, and organize them into a systems typology for conservation. This step will also design innovative indicators to map how threats vary and interact in space and time. I will apply and test these concepts globally, for the poorly studied tropical dry forests. STEP 2 will empirically validate these concepts for two tropical dry forests regions in South America. Comparative social-ecological fieldwork will reveal how threats impact biodiversity, how land-use actors relate to threats, and how conservation actions influence actors. This will enable a major advance in conservation planning methods to consider land-use actors, dynamic threats, and to rigorously evaluate when, where, and at which scale conservation is most effective. STEP 3 will integrate the project results to provide generalized insights into conservation challenges and opportunities in tropical dry forests globally. My project will cross-fertilise between land system science and conservation science and link to international science-policy dialogues, laying the foundation for a new research agenda integrating complex land systems into biodiversity conservation.

Mots-clés : land system science,social ecological systems,sustainability science,conservation science
Projet ERC : LIFEPLAN (Horizon 2020, appel 2019, Synergy grants)
Entité participante : University of Helsinki — Pays : Finlande — Rôle : Partner
Acronyme de l'entité : UH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3744915.0 €

Biodiversity underlies ecosystem functioning. To achieve the basis for a sustainable management of natural resources under current environmental change, we thus need a unified theory of the forces structuring vast sets of ecosystems and taxonomical groups on Earth. For the first time, such a synthesis is now within reach, based on a recent revolution in sampling methodology, globally relevant ecological data, and advances in statistical methods for linking immense data to community ecological theory. In LIFEPLAN, we bring together the key expertise needed to generate and interpret Big Ecological Data for a global synthesis of biotic patterning across our planet: world leaders in community ecology, methods for automated species recognition, and Bayesian statistics for immense data. Our objectives are to generate a new understanding of biodiversity patterns and dynamics by developing fundamentally new methods for big data statistics. To this end, we will generate fully standardized, global big data on a range of species groups, thus allowing quantification of variation in ecological communities at spatial scales covering six orders of magnitude (from 0.1 km to 10000 km), across tens of thousands of species. The resulting data motivate the development of transformative big data statistics, in particular highly scalable algorithms for spatio-temporal data, as well as methods for automated species identification from DNA, audio and image samples. As a key deliverable, we will develop global joint species distribution models describing the spatio-temporal structure of life on Earth. Working together will allow each of us to tackle what we regard as the ultimate challenges in our own fields, while simultaneously collaborating around solutions changing the face of modern biodiversity science. Now is the time for this project, as the big data and big methods emerging today coincide with a great need for global understanding of biodiversity structure and dynamics.

Mots-clés : global patterning of life,big data science,automated species recognition,high throughput data generation,community ecology,biodiversity science,bayesian statistics,scalable methods,hierarchical patterns and processes,joint species distribution modelling
Projet ERC : LIFEPLAN (Horizon 2020, appel 2019, Synergy grants)
Entité participante : University of Jyväskylä — Pays : Finlande — Rôle : CO-PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 500000.0 €

Biodiversity underlies ecosystem functioning. To achieve the basis for a sustainable management of natural resources under current environmental change, we thus need a unified theory of the forces structuring vast sets of ecosystems and taxonomical groups on Earth. For the first time, such a synthesis is now within reach, based on a recent revolution in sampling methodology, globally relevant ecological data, and advances in statistical methods for linking immense data to community ecological theory. In LIFEPLAN, we bring together the key expertise needed to generate and interpret Big Ecological Data for a global synthesis of biotic patterning across our planet: world leaders in community ecology, methods for automated species recognition, and Bayesian statistics for immense data. Our objectives are to generate a new understanding of biodiversity patterns and dynamics by developing fundamentally new methods for big data statistics. To this end, we will generate fully standardized, global big data on a range of species groups, thus allowing quantification of variation in ecological communities at spatial scales covering six orders of magnitude (from 0.1 km to 10000 km), across tens of thousands of species. The resulting data motivate the development of transformative big data statistics, in particular highly scalable algorithms for spatio-temporal data, as well as methods for automated species identification from DNA, audio and image samples. As a key deliverable, we will develop global joint species distribution models describing the spatio-temporal structure of life on Earth. Working together will allow each of us to tackle what we regard as the ultimate challenges in our own fields, while simultaneously collaborating around solutions changing the face of modern biodiversity science. Now is the time for this project, as the big data and big methods emerging today coincide with a great need for global understanding of biodiversity structure and dynamics.

Mots-clés : global patterning of life,big data science,automated species recognition,high throughput data generation,community ecology,biodiversity science,bayesian statistics,scalable methods,hierarchical patterns and processes,joint species distribution modelling
Projet ERC : IntegraBrain (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : University of Sheffield — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1328536.94 €

Bioelectronic medicine may soon replace systemic drugs for treating some chronic conditions. The clinician will implant a miniature laboratory to deliver and coordinate a multi-modal treatment program directly at the affected tissue. The technology to bring this vision to the clinic is not yet available. The IntegraBrain project will contribute by building an implantable network of sensors and actuators. Actuators will deploy electricity, light, drugs and thermal energy as modalities of the therapeutic program, while sensors will monitor its progress. A key technological advance will be a method for direct writing of the sensor-actuator network. To achieve this, we will develop a palette of functional inks where each ink supports one of the therapeutic modalities. The technology has the potential to be tailored for applications in soft tissue organs, especially in the nervous system, where injury or degeneration can result in chronic disability. We will apply IntegraBrain technology in two niches of the nervous system in rodents. In the central nervous system, we will demonstrate seizure control by multi-modal neuromodulation. In the peripheral nervous system, we will demonstrate reversible block and excitation. For the first time, we will observe if multi-modal neuromodulation leads to synergistic effects on the nervous system. With the IntegraBrain project, we hope to catalyse pre-clinical development of implantable human-machine interfaces for therapeutic applications.

Mots-clés : bioelectronics,implant,multi modal,neuromodulation
Projet ERC : Microrobots (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : University of Exeter — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1766481.0 €

Biohybrid MicroRobots (BMRs) are conceptual microscopic robotic devices that combine synthetic and biological components and can be remote controlled to a specific destination, attach to a target and perform a bespoke biochemical operation at nanoscale precision. Within the 5-year Microrobots project, I intend to develop innovative BMRs by combining magnetic swimmers (MSs) with prokaryotic S-layers (SLs). MSs are microscopic devices that consist of two flexibly linked metallic beads with different magnetic properties and can be remote controlled through liquid media, simply by applying oscillating magnetic fields. SLs are highly stable 2-dimensional protein arrays that form resilient cell wall components in archaea and bacteria and can be genetically modified and reassembled on inorganic surfaces. I will introduce affinity tags into selected archaeal and bacterial SLs and reassemble them on the surfaces of MSs. This will coat MSs with unique affinity matrices, on which bioactive molecules can be conjugated at regular arrays, high density and defined distance. Through this strategy, I will generate BMRs that can be equipped with any bioactive functionality provided by nature, such as adhesive filaments, enzymes, antibodies, reporters, drug cargo or any other thinkable functional molecule. The BMRs that I will develop will elegantly miniaturise robotics and enable us to deliver bioactivity at nanometre precision. This will provide a revolutionary platform technology that will be applicable in a plethora of fields, such as medicine, nanotechnology, environmental engineering or scientific exploration and generate a real step change in the ways in which we build new materials, engineer our environment, fight disease and explore the universe in the 21st century.

Mots-clés : cryoem,magnetic swimmers,s layers,adhesive filaments,affinity tags
Projet ERC : FLUOSWITCH (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
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 : 851562.5 €

Biological imaging is essential for revealing the inner workings of living systems. Among the numerous imaging modalities, light microscopy has revolutionized biological research. In addition to advances in optics and detectors, imaging has benefited from the development of molecular tools to observe biomolecules in action. Although the last decade’s breakthroughs in imaging have led to new discoveries in biology, there are still extraordinary opportunities for basic and clinical research in further advancing imaging capabilities. This project proposes to develop new classes of probes to advance biological imaging and allow the study of biological processes in all their complexity. First, I propose to push the boundaries of multiplexing and super-resolution imaging in living cells developing a new class of fluorogenic probes that act as genetically encoded fluorescence on/off switches. Highly multiplexed images will be built up over sequential activation of orthogonal fluorescence on/off switches, while continuous switching will allow implementing innovative dynamic super-resolution techniques in living cells. Then, I will develop dynamic fluorescence on/off switches enabling to reveal the dynamics of intracellular processes, focusing in particular on the visualization of interaction dynamics in real-time, and the dynamic detection of endogenous molecules (e.g. proteins, nucleic acids) in living cells. The final part will be dedicated to the development of probes acting as molecular integrator switches to identify active cell circuits in whole tissues or organisms through permanent labeling of transiently activated cells. Overall, this project will enable to push back the frontiers of biological imaging providing innovative tools to interrogate quantitatively and comprehensively living systems at the molecular, cellular and network levels.

Mots-clés : biomolecular imaging,fluorescence,probe and biosensor design
Projet ERC : MicMactin (Horizon 2020, appel 2015, Starting 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 : 1491868.0 €

Biological motion and forces originate from mechanically active proteins operating at the nanometer scale. These individual active elements interact through the surrounding cellular medium, collectively generating structures spanning tens of micrometers whose mechanical properties are perfectly tuned to their fundamentally out-of-equilibrium biological function. While both individual proteins and the resulting cellular behaviors are well characterized, understanding the relationship between these two scales remains a major challenge in both physics and cell biology. We will bridge this gap through multiscale models of the emergence of active material properties in the experimentally well-characterized actin cytoskeleton. We will thus investigate unexplored, strongly interacting nonequilibrium regimes. We will develop a complete framework for cytoskeletal activity by separately studying all three fundamental processes driving it out of equilibrium: actin filament assembly and disassembly, force exertion by branched actin networks, and the action of molecular motors. We will then recombine these approaches into a unified understanding of complex cell motility processes. To tackle the cytoskeleton's disordered geometry and many-body interactions, we will design new nonequilibrium self consistent methods in statistical mechanics and elasticity theory. Our findings will be validated through simulations and close experimental collaborations. Our work will break new ground in both biology and physics. In the context of biology, it will establish a new framework to understand how the cell controls its achitecture and mechanics through biochemical regulation. On the physics side, it will set up new paradigms for the emergence of original out-of-equilibrium collective behaviors in an experimentally well-characterized system, addressing the foundations of existing macroscopic "active matter" approaches.

Mots-clés : theory,active matter,cytoskeleton,actin
Projet ERC : ROBOCHIP (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1748773.0 €

Biological organisms have spectacular three-dimensional morphologies in which correct multiscale organization and physicochemical regulation are essential for proper function. Understanding the dynamic interactions among cells connected through a structurally complex three-dimensional (3D) fibre network requires a rigorous system identification effort and engineering analysis. To develop accurate and comprehensive models of cell sociology, we need to identify how several different components act together as a connected system and define high-order emergent programs that constitute layers of signals in time and space. The objective of this proposal is to engineer new microrobotic technologies that can be seamlessly integrated with high-throughput bioengineering platforms and produce physiologically relevant signals to establish an active dialogue with the members of the tissue community and drive the cell-network evolution. We propose to build cutting-edge robotic micromanipulation systems to perform automated operations on 3D biological samples with exceptional dexterity and high spatiotemporal resolution. Wirelessly powered micromachines will modulate local mechanochemical signaling within the tissues and move through fibrillar scaffolds. Multi-functional integrated platforms will simultaneously apply external and internal signals, and advanced imaging systems will visualise whole tissue activity at the cellular resolution. Our data will be used to establish computational models of tissue-level mechanical response to dynamical perturbations with particular focus on transmission of signals and feedback mechanisms. The ability to hack cellular communication links and interfere with the biological processes in 3D systems will lead to a better understanding of morphogenesis and regeneration, and can aid in developing treatments that ensures a microenvironment with a distribution of signals that minimizes disease progression.