Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ZebraZoom (Horizon 2020, appel 2018, Proof of concept grants)
Entité participante : Institut du cerveau — Pays : France — Rôle : PI
Acronyme de l'entité : ICM
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

With millions of European citizens suffering from chronic pain and neurodegenerative disease, there is an urgent need for efficient solutions for drug screening in animal models. Discovery of new drugs and functions of genes involved in these human diseases relies on efficient ways to screen effects on animal behavior and at low cost. Zebrafish emerged in the last decade as an essential model for drug discovery as it is: i) a low cost genetic model organism whose genome shares 70% homology with human’s. ii) well-suited to fast and high throughput investigation of genes and molecules. iii) an ideal platform to study genes and pathways of relevance to disease in humans. Consequently, several companies are exploiting zebrafish research to devise new drugs for motor and neurological disorders. However, the current state of the art in commercial analysis of zebrafish behavior is limited to the analysis of crude parameters. In these conditions, the fast kinematics indicative of specific types of sensory and motor defects cannot be resolved. A fine kinematic analysis efficiently performed over large population of animals is crucial to reliably quantify defects in strength, posture or speed in mutant animals with and without with drug treatment. This accuracy is critical for concluding on the effects of drugs involved in motor functions, posture or pain. During her ERC starting grant OptoLoco, Dr. Wyart has developed ZebraZoom to resolve kinematic data with the necessary degree of resolution required for interpretation of motor defects. This approach enables the quantitative measurement of defects in speed, posture, and movement strength. In the ZebraZoom PoC, we will evaluate the market potential for a high-throughput method to quantify and categorise behavioural movements of zebrafish larvae/juveniles in response to drug administration and genetic manipulations and elaborate a marketing plan and business plan targeting for pharmaceutical companies and research labs.

Mots-clés : high throughput drug and genetic screening,zebrafish,locomotion
Projet ERC : MAMSIE (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Acronyme de l'entité : KUL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2498941.0 €

With the CoRoT & Kepler data analysed, the time is optimal to move from observational asteroseismology to innovative stellar modelling of the steal factories of the Universe. With MAMSIE, we follow the footsteps of helioseismologists some 30 years after them, but this time we shall be developing inversion methods for stellar structure based on gravity-mode oscillations that probe the deep stellar interior. MAMSIE will lead to new models for a variety of single and binary stars with masses between 3 and 30 M⊙ whose space photometry and high-resolution spectroscopy reveal sufficient seismic information on their gravity modes to invert the frequencies and compute the stars’ structure. In contrast to the conventional theoretical approach to stellar evolution, the data-driven approach of MAMSIE will allow us to include angular momentum transport due to internal gravity waves, as well as mixing prescriptions for turbulent entrainment, from coupling of the output of 3D hydrodynamical simulations of these phenomena to specialised seismic observables of relevance for massive stars. Our sample includes slow and fast rotators, with and without a magnetic field, with and without a stellar wind. The new models will be placed in an evolutionary context for optimal assessment of the evolution of internal rotation, angular momentum, and chemical mixing throughout stellar life of massive stars. The output of the stellar modelling will provide fundamentals for all topics in modern astrophysics that rely on massive star models. MAMSIE is overarching and will require a multidisciplinary team led by an expert in gravity-mode oscillations working in close collaboration with a 3D hydrodynamics expert; it will offer a highly competitive environment for PhD and postdoctoral research on the astrophysics of massive stars.

Mots-clés : stellar structure,stellar evolution,massive stars,asteroseismology,high precision space photometry
Projet ERC : ENSURE (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Politecnico di Milano — Pays : Italie — Rôle : PI
Acronyme de l'entité : POLIMI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1887500.0 €

With the ENSURE project I aim at attaining ground-breaking results in the field of superintense laser-driven ion acceleration, proposing a multidisciplinary research program in which theoretical, numerical and experimental research will be coherently developed in a team integrating in an unprecedented way advanced expertise from materials engineering and nanotechnology, laser-plasma physics, computational science. The aim will be to bring this topic from the realm of fundamental basic science into a subject having realistic engineering applications. The discovery in 2000 of brilliant, multi-MeV, collimated ion sources from targets irradiated by intense laser pulses stimulated great interest worldwide, due to the ultra-compact spatial scale of the accelerator and ion beam properties. The laser-target system provides unique appealing features to fundamental physics which can be studied in a small lab. At the same time, laser-ion beams could have future potential in many technological areas. This is boosting the development of new labs and facilities all over Europe, but to support these efforts, crucial challenges need to be faced to make these applications a reality. The goals of ENSURE are: i) design and production of nanoengineered targets, with properties tailored to achieve optimized ion acceleration regimes. This will be pursued exploiting advanced techniques of material science & nanotechnology ii) design of laser-ion beams for novel, key applications in nuclear and materials engineering iii) realization of engineering-oriented ion acceleration experiments, in advanced facilities iv) synergic development of all the required theoretical support for i,ii,iii). The results of the project can determine a unique impact in the research on laser-driven ion acceleration in Europe, providing new directions to support the attainment, in the next future, of concrete applications of great societal relevance, in medical, energy and materials areas.

Mots-clés : laser plasma interaction,nanotechnology,nuclear engineering,thin films,nuclear science,ion beam diagnostics,materials irradiation,particle accelerators,relativity,non linear physics
Projet ERC : GEM (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 1498570.0 €

With the considerable advance of automatic image-based capture in Computer Vision and Computer Graphics these latest years, it becomes now affordable to acquire quickly and precisely the full 3D geometry of many mechanical objects featuring intricate shapes. Yet, while more and more geometrical data get collected and shared among the communities, there is currently very little study about how to infer the underlying mechanical properties of the captured objects merely from their geometrical configurations. The GEM challenge consists in developing a non-invasive method for inferring the mechanical properties of complex objects from a minimal set of geometrical poses, in order to predict their dynamics. In contrast to classical inverse reconstruction methods, my proposal is built upon the claim that 1/ the mere geometrical shape of physical objects reveals a lot about their underlying mechanical properties and 2/ this property can be fully leveraged for a wide range of objects featuring rich geometrical configurations, such as slender structures subject to frictional contact (e.g., folded cloth or twined filaments). To achieve this goal, we shall develop an original inverse modeling strategy based upon a/ the design of reduced and high-order discrete models for slender mechanical structures including rods, plates and shells, b/ a compact and well-posed mathematical formulation of our nonsmooth inverse problems, both in the static and dynamic cases, c/ the design of robust and efficient numerical tools for solving such complex problems, and d/ a thorough experimental validation of our methods relying on the most recent capturing tools. In addition to significant advances in fast image-based measurement of diverse mechanical materials stemming from physics, biology, or manufacturing, this research is expected in the long run to ease considerably the design of physically realistic virtual worlds, as well as to boost the creation of dynamic human doubles.

Mots-clés : inverse modelling,nonsmooth mechanics,frictional contact,dynamics of slender structures,physically guided shape reconstruction
Projet ERC : SILENT (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : University of Liège — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1431400.0 €

With the first direct detection of gravitational waves on the 14th of September 2015, a new window has been opened on the Universe. This was the starting point of new science, complementary to the measurement of electromagnetic signals by optical telescopes. Since that date, several detections have been made, offering wonderful validation of Einstein’s theory of general relativity, and extraordinary insight on the dynamics of heavy black hole binaries and binaries of neutron stars. The exploration of the Universe through this new window using Earth-based instruments will continue with more sensitive instruments, but will ultimately depend on our capability to isolate them from the two main sources of low-frequency disturbances on Earth: seismic activity and fluctuations of gravity field (Newtonian noise). Due to the extremely small amplitude of gravitational waves, it is a prior concern to carefully isolate the detector from any type of disturbance. In order to address the aforementioned limitations, this project proposes to develop a completely novel platform, controlled by optical seismometers, liquid inclinometers and a gravimeter. It will virtually float in the inertial space, decoupled from ground motion for periods at least as large as 100 seconds. The controlled platform will be the most stable ever build on Earth. Such performance will be obtained thanks to a revolutionary approach, combining three major innovations: (1) Novel optical inertial sensors, (2) Efficient controllers, combining sensor fusion methods, and dedicated mechatronic architectures, (3) Direct measurement of Newtonian noise. This project will contribute to prepare the third generation of low-frequency gravitational wave detectors. The outcomes will be also applicable to a large class of other instruments (e.g. particle colliders, atomic force microscopes, lithography machines, medical imaging instruments), ensuring a generic character to this project, and a major scientific impact.
Projet ERC : DYMO (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Heinrich Heine University Düsseldorf — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HHU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499956.0 €

With the prevalence of information technology in our daily lives, our ability to interact with machines in increasingly simplified and more human-like ways has become paramount. Information is becoming ever more abundant but our access to it is limited not least by technological restraints. Spoken dialogue systems address this issue by providing an intelligent speech interface that facilitates swift, human-like acquisition of information. The advantages of speech interfaces are already evident from the rise of personal assistants such as Siri, Google Assistant, Cortana or Amazon Alexa. In these systems, however, the user is limited to a simple query, and the systems attempt to provide an answer within one or two turns of dialogue. To date, significant parts of these systems are rule-based and do not readily scale to changes in the domain of operation. Furthermore, rule-based systems can be brittle when speech recognition errors occur. The vision of this project is to develop novel dialogue models that provide natural human-computer interaction beyond simple information-seeking dialogues and that continuously evolve as they are being used by exploiting both dialogue and non-dialogue data. Building such robust and intelligent spoken dialogue systems poses serious challenges in artificial intelligence and machine learning. The project will tackle four bottleneck areas that require fundamental research: automated knowledge acquisition, optimisation of complex behaviour, realistic user models and sentiment awareness. Taken together, the proposed solutions have the potential to transform the way we access information in areas as diverse as e-commerce, government, healthcare and education.

Mots-clés : statistical spoken dialogue systems
Projet ERC : HADES (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Southern Denmark — Pays : Danemark — Rôle : PI
Acronyme de l'entité : SDU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3075736.14 €

With this project, called HADES, we aim to provide the first detailed, combined analysis of benthic diagenesis and microbial ecology of some of the deepest oceanic trenches on Earth. We argue that deep trenches, some of the most remote, extreme, and scantly explored habitats on Earth, are hotspots of deposition and mineralization of organic material. With the development of novel autonomous in situ instrumentation to overcome large sampling artifacts from decompression, we will i) determine rates of benthic metabolism and the importance of the deep trenches for the marine carbon and nitrogen cycles, ii) explore the unique benthic microbial communities driving these processes, and iii) investigate the proposed great role of virus in regulating microbial performance and carbon cycling in hadal sediments. By comparing trenches from contrasting oceanic settings the project provides a completely novel general analysis of hadal biogeochemistry and the role of deep trenches in the oceans, as well as fundamental new insights into the composition and functioning of microbial communities at extreme pressure.

Mots-clés : marine,deep sea research,hadal trenches,in situ instrumentation,microbiology
Projet ERC : MatMech (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Copenhagen — Pays : Danemark — Rôle : PI
Acronyme de l'entité : UCPH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1493269.0 €

With this proposal, I want to develop a new, multimodal approach to in situ X-ray scattering studies to unravel formation mechanisms of the solid state. The aim of the project is to develop a unified view of metal oxide nucleation processes on the atomic scale: From precursor complexes over pre-nucelation clusters to the final crystalline particle. The development of new materials relies on our understanding of the relation between material structure, properties and synthesis. While the intense focus on ‘materials by design’ have made it possible to predict the properties of many materials given an atomic arrangement, actually knowing how to synthesize it is a completely different story. Material synthesis methods are to a large degree developed by extensive parameter studies based on trial-and-error experiments. Specifically, our knowledge of particle nucleation is lacking, as even non-classical views on nucleation such as the concept of pre-nucleation clusters do not apply an atomistic view of the formation process. Here, I want to use new methods in X-ray total scattering and Pair Distribution Function analysis to follow nucleation processes to establish the framework needed for predictive material synthesis. One of the large challenges in studying nucleation is the lack of a characterization method that can give structural information on materials without long-range order. I have demonstrated that time-resolved X-ray total scattering gives new possibilities for following structural changes in a synthesis, and the use of total scattering has opened for a new view on material formation. However, the complexity of the structures involved in nucleation processes is too large to obtain sufficient information from X-ray total scattering alone. Here, I will combine X-ray total scattering data with complementary techniques using a new multimodal approach for complex modelling analysis, providing a unifying view on material nucleation.

Mots-clés : x ray scattering,in situ,nucleation
Projet ERC : FHiCuNCAG (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : University of Antwerp — Pays : Belgique — Rôle : PI
Acronyme de l'entité : UAntwerp
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1171360.0 €

With this research programme, inspired by open problems within noncommutative algebraic geometry (NCAG) as well as by actual developments in algebraic topology, it is our aim to lay out new foundations for NCAG. On the one hand, the categorical approach to geometry put forth in NCAG has seen a wide range of applications both in mathematics and in theoretical physics. On the other hand, algebraic topology has received a vast impetus from the development of higher topos theory by Lurie and others. The current project is aimed at cross-fertilisation between the two subjects, in particular through the development of “higher linear topos theory”. We will approach the higher structure on Hochschild type complexes from two angles. Firstly, focusing on intrinsic incarnations of spaces as large categories, we will use the tensor products developed jointly with Ramos González and Shoikhet to obtain a “large version” of the Deligne conjecture. Secondly, focusing on concrete representations, we will develop new operadic techniques in order to endow complexes like the Gerstenhaber-Schack complex for prestacks (due to Dinh Van-Lowen) and the deformation complexes for monoidal categories and pasting diagrams (due to Shrestha and Yetter) with new combinatorial structure. In another direction, we will move from Hochschild cohomology of abelian categories (in the sense of Lowen-Van den Bergh) to Mac Lane cohomology for exact categories (in the sense of Kaledin-Lowen), extending the scope of NCAG to “non-linear deformations”. One of the mysteries in algebraic deformation theory is the curvature problem: in the process of deformation we are brought to the boundaries of NCAG territory through the introduction of a curvature component which disables the standard approaches to cohomology. Eventually, it is our goal to set up a new framework for NCAG which incorporates curved objects, drawing inspiration from the realm of higher categories.

Mots-clés : noncommutative algebraic geometry  14a22,18e15,homological and homotopical algebra  14f05,18g55,55p42,higher topos theory  18g30,operads  18d50
Projet ERC : LineageDiscovery (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Weizmann Institute of Science — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2250000.0 €

Within a decade, advances in single-cell genomics would allow humanity to embark on a coordinated international effort to discover the human cell lineage tree. The goal of LineageDiscovery is to lay the biological, computational and architectural foundations for this envisioned project and demonstrate its feasibility and value. An organismal cell lineage tree is a rooted, labelled binary tree where nodes represent organism cells, edges represent progeny relations and labels capture cell state. The tree of an adult human has about 100 trillion nodes. Many fundamental open questions in biology and medicine are about the structure, dynamics and variance of the human cell lineage tree in development, health, ageing and disease. E.g., which cancer cells give rise to metastases? Do beta cells renew? Which progeny do brain stem cells produce in development, maintenance and ageing? LineageDiscovery is based on a decade of research on this challenge by Shapiro’s lab and others. It will develop an efficient biological-computational cell lineage discovery workflow that starts with sampled cells and ends with knowledge of their cell lineage tree; and a scalable architecture for the collaborative development and the distributed deployment of this workflow. The workflow will be based on emerging single-cell technologies and will include novel algorithms to analyse single-cell data, to reconstruct cell lineage trees, and to infer ancestral cell type and state dynamics. A programmable meta-system will be developed and used for workflow optimization and evaluation. The workflow and architecture will be deployed and tested in a broad range of proof-of-concept human cell lineage discovery experiments with self-funded collaborators. Successful execution of this research plan coupled with expected advances in single-cell genomics would establish both the feasibility and the value of the envisioned large-scale human cell lineage discovery project, ideally leading to its launch.

Mots-clés : human cell lineage tree,whole organism science,single cell genomics,cell lineage reconstruction algorithms,bioinformatics and system biology