Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : FanCY (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Delft University of Technology — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU Delft
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

The aim of this proposal is to understand when, how and why metastatic tumour cells detach from a tumour. Often, primary tumours do not kill patients, but secondary tumours do. These so-called metastatic tumour cells disassociate from a primary tumour and, ultimately, prove fatal. Currently, we do not understand the fundamentals of the biophysical pathways and mechanisms of the metastasis of cancer, hampering medical intervention. I propose a multidisciplinary approach, combining engineering, chemistry, biophysics and cell biology to identify the mechanical pathways for the creation of metastatic cancer cells. Biological cells in tissue are very densely packed, which locks them in place relative to their neighbours, a state referred to as jammed. The collective system of cells can become fluidised locally and flow when pushed or deformed. Even greater forces can make the entire tissue fluid-like, referred to as yielding. The crucial open questions are: how does tissue yield, and what universal physics underlies yielding? I will develop a novel fundamental and predictive description of yielding in jammed living tissue to show: 1. How and when jammed living cells are driven to fluid-like state. 2. How confinement tunes the migration mode of cancer cells. 3. How yielding is related to the structural evolution of detached cells. 4. How critical scaling controls deformation and flow of living cells near yielding. I will demonstrate that the distance to yielding governs the mechanical response in collective cell motion inside a tumour, and that exploiting critical scaling allows predicting the dynamics of cell detachment near yielding. The outcomes will significantly aid the treatment of cancer in the near future by bridging the gap between chemical and mechanical pathways of cancer metastasis. I have the required multidisciplinary track record. Moreover, preliminary experiments show highly promising results.

Mots-clés : biological soft matter,cell jamming,cell unjamming,physics of cancer
Projet ERC : PREDICT (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : Bielefeld University — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1658012.0 €

The algorithmic turn of prediction, connected with Big Data and Machine Learning, presents an exciting and urgent challenge for the social sciences. Recent advances in digital forecasting claim to provide a predictive score for individual persons or singular events, thereby introducing a new way to manage the uncertainty of the future. But knowing the future in advance is not only advantageous. In fact, for our society, uncertainty about the future is also a resource. Since modernity, with the support of probability calculus various social institutions in different domains have developed means of coping with ignorance of the future by starting with the one thing that we all share – uncertainty. What happens to the stabilized forms of management of the future when their first resource – shared uncertainty – is missing? There is still no systematic research on this groundbreaking transformation. This project proposes a set of theory-driven empirical studies of the transition from probabilistic forms of uncertainty management to the new algorithmic forms of prediction. We will investigate three important social areas highlighting three fundamental dimensions with which digital forecast must deal. 1) First we will focus on personalized insurance. Here the key dimension is individualization of prediction, where the challenge is that such prediction could undermine the mutualization principle organized around actuarial practices. 2) Our second research area is precision medicine, highlighting the dimension of generalization where the challenge is the combination of algorithmic procedures with established statistical methods. 3) In the third field, predictive policing underscores the problem of bias while it challenges the distinction between prevention and repression. Exploring these transformation and its consequences, the project aims at developing a comprehensive approach to study the social, technical and theoretical aspects of prediction in digital society

Mots-clés : sociology of algorithms,prediction,precision medicine,predictive policing,sociology of risk,insurance
Projet ERC : VIBRATE (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Eindhoven University of Technology — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU/e
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2429322.5 €

The amplification of collective molecular effects to macroscopic deformation is one of the most intriguing challenges in materials science. Individual molecules can be reversibly activated by various means such as light, chemicals and external electrical or magnetic fields. They may respond by changing their orientation, their molecular conformation or by breaking /forming chemical bonds. Bringing these molecules in a matrix of an ordered molecular system, such as a liquid crystal polymer network, introduces molecular cooperativity and directionality. Dimensional changes of the individual molecules add up to large effects such as the formation of deformed surfaces in a coating and the formation of free volume (molecular voids) in membranes. The objective of the present proposal is to bring the molecular action, in conjunction with the macroscopic deformation, out of its equilibrium aiming a self-sustaining oscillation of the macroscopic response to a continuous trigger. An example that will be investigated is a surface that continuously changes it topography when addressed by its trigger. Another example is a membrane that will oscillate its (localized) free volume thus providing an active transport mechanism for species through the membrane. Alternatively we will investigate the response to an oscillating trigger with a frequency matching the molecular action to find sweet spots for mechanical resonance thus enhancing the macroscopic effect. The research is challenging. Only, with a comprehensive and combined effort, we can expect the required progress needed to close the gap between materials science, optics, electronics and mechanics and to deliver routes to new applications. But when achieved it will undoubtfully lead to new applications in coating and film technology with an outlook to soft robotics, self-pumping membranes, mechanical communication at man-machine interfaces and energy harvesting.

Mots-clés : responsive polymers,oscillating surfaces,oscillating membranes
Projet ERC : LTCSEI (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : École d'économie de Paris — Pays : France — Rôle : PI
Acronyme de l'entité : EEP
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1187927.37 €

The analogy-based expectation equilibrium (Jehiel, 2005) has been introduced to cope with strategic environments in which agents form their expectations by bundling data that come from different sources (see also the valuation equilibrium defined in Jehiel and Samet, 2007). An essential next step is to make progress on when and how subjects bundle data to facilitate learning. Various principles are proposed to discipline the choices of analogy partitions in ABEE and of similarity classes in VE: the observation-based principle views the bundling as a consequence of a lack of accessibility to missing information in past interactions, the psychologically-based principle views categorizations as the consequence of observed similarity in early interactions, the culturally-based principle views the bundling of actions into similarity classes either as a consequence of a common labelling of actions or as a consequence of ethical considerations that lead us to think of different actions as having similar consequences. The impact of such principles will be studied both theoretically and experimentally with the goals of explaining a number of new phenomena and shifting the conventional wisdom in behavioural economics that has pointed out a number of anomalies in behaviors without systematically relating them to imperfections in the learning process. In addition, I will be concerned with the aggregation of different types of feedback such as data on one own performance or data on others’ attitudes in multi-context environments, as well as putting the proposed approach of learning through categories in the broader perspective of the literature on bounded rationality

Mots-clés : learning through categories,bounded rationality,heuristics
Projet ERC : LTCSEI (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : École nationale des ponts et chaussées — Pays : France — Rôle : Partner
Acronyme de l'entité : ENPC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 182507.13 €

The analogy-based expectation equilibrium (Jehiel, 2005) has been introduced to cope with strategic environments in which agents form their expectations by bundling data that come from different sources (see also the valuation equilibrium defined in Jehiel and Samet, 2007). An essential next step is to make progress on when and how subjects bundle data to facilitate learning. Various principles are proposed to discipline the choices of analogy partitions in ABEE and of similarity classes in VE: the observation-based principle views the bundling as a consequence of a lack of accessibility to missing information in past interactions, the psychologically-based principle views categorizations as the consequence of observed similarity in early interactions, the culturally-based principle views the bundling of actions into similarity classes either as a consequence of a common labelling of actions or as a consequence of ethical considerations that lead us to think of different actions as having similar consequences. The impact of such principles will be studied both theoretically and experimentally with the goals of explaining a number of new phenomena and shifting the conventional wisdom in behavioural economics that has pointed out a number of anomalies in behaviors without systematically relating them to imperfections in the learning process. In addition, I will be concerned with the aggregation of different types of feedback such as data on one own performance or data on others’ attitudes in multi-context environments, as well as putting the proposed approach of learning through categories in the broader perspective of the literature on bounded rationality

Mots-clés : learning through categories,bounded rationality,heuristics
Projet ERC : TB-RECONNECT (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana — Pays : Espagne — Rôle : Partner
Acronyme de l'entité : FISABIO
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

The annual decline in tuberculosis (TB) incidence is not greatly different from that of the ‘90s, when no coordinated efforts in global tuberculosis control were in place. The failure of current TB control programmes to accelerate TB elimination has multiple causes, including losses of TB cases at the different steps of the TB care cascade, and a chronic lack of funding hampering innovation. Additionally, we have failed to halt transmission in many settings, as we have failed to incorporate our improved understanding of transmission in TB control programmes. Our current approach to controlling TB is focused on a narrow view of who is transmitting the disease (symptomatically active TB cases), while there is a growing consensus that the traditional latent/active dichotomy is no longer valid, and that asymptomatic individuals with active TB signatures are also likely to be transmitting the disease. There is a critical lack of high-resolution data from different settings on the contribution to the transmission burden of cases with different infection statuses. To fill this evidence gap, I propose synergizing three recent TB research developments; We can now use host blood transcriptomics to discriminate between infection status within the latent pool of individuals. We can now quantify transmission at a resolution not previously available, using pathogen genome sequencing. We can now use phylogenetic and epidemiological models to identify when transmission has happened. Combining these three key developments with TB cohorts from multiple settings, and available tools from bacterial population genetics, high-throughput functional genomics and infection biology, we will be in a key position to answer these burning questions about the nature of TB transmission and the host and pathogen biology behind this. More importantly, we will reconnect transmission to TB control, to inform major shifts in global and local control strategies.

Mots-clés : tuberculosis,epidemiology,global health,infectious diseases,pathogen genomics,host transcriptomics,infection models
Projet ERC : METAFOAM (Horizon 2020, appel 2018, 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 : 1999677.0 €

The astounding properties of metamaterials result from a characteristic spatial organisation of purpose-designed structural units. Research on metamaterials has greatly advanced thanks to their reliable top-down fabrication (lithography, 3D-printing,...). For large-scale production, however, smart bottom-up design strategies are required, for example through self-assembly of the structural units. While this has been developed for thermally-driven systems with sub-micrometric units, no systematic design strategies are established for mechanically-driven systems with larger units. The METAFOAM project will fill this gap by addressing the scientific challenges towards controlled bottom-up structuring of bubble/drop packings in liquid foam/emulsion templates. While “ordinary” foams/emulsions have been investigated in depth, the control over their structure is very limited. The METAFOAM project will provide access to very different structures by explicitly tuning the bubble/drop interactions through the presence of a polymeric skin with controlled repulsive, adhesive and frictional properties. We will develop methods to reliably create/characterise these skins and establish a state diagram which systematically relates the resulting bubble/drop interactions and the foam/emulsion structure. Solidification of the most promising structures will provide new types of cellular polymers with currently inaccessible mechanical or acoustic meta-properties: high stiffness-to-weight-ratios, negative Poisson ratios, and acoustic band-gap properties. The impact of this interdisciplinary project at the interface between physics and chemistry is therefore two-fold. In the liquid state it will advance our understanding of the a-thermal packing of very soft objects with tuneable interactions, linking the physics of granular media and biological tissues. In the solid state it will provide new cellular systems for the fabrication and investigation of mechanical and acoustic metamaterials.

Mots-clés : polymers at interfaces,interfacial rheology,foams,emulsions,soft granular media,cellular polymers,mechanical meta materials,acoustic meta materials
Projet ERC : ECHO (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Bonn — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1525840.0 €

The automated analysis of visual data is a key enabler for industrial and consumer technologies and of immense economic and social importance. Its main challenge is in the inherent ambiguity of images due to the very mechanism of image capture: light reaching a pixel on different paths or at different times is mixed irreversibly. Consequently, even after decades of extensive research, problems like deblurring or descattering, geometry/material estimation or motion tracking are still largely unsolved and will remain so in the foreseeable future. Transient imaging (TI) tackles this problem by recording ultrafast optical echoes that unmix light contributions by the total pathlength. So far, TI used to require high-end measurement setups. By introducing computational TI (CTI), we paved the way for a lightweight capture of transient data using consumer hardware. We showed the potential of CTI in scenarios like robust range measurement, descattering and imaging of objects outside the line of sight – tasks that had been considered difficult to impossible so far. The ECHO project is rooted in computer graphics and computational imaging. In it, we will overcome the practical limitations that are hampering a large-scale deployment of TI: the time required for data capture and to reconstruct the desired information, both in the order of seconds to minutes, a lack of dedicated image priors and of quality guarantees for the reconstruction, the limited accuracy and performance of forward models and the lack of ground-truth data and benchmark methods. Over the course of ECHO, we will pioneer advanced capture setups and strategies, signal formation models, priors and numerical methods, for the first time enabling real-time reconstruction and analysis of transient light transport in complex and dynamic scenes. The methodology developed in this far-reaching project will turn TI from a research technology into a family of practical tools that will immediately benefit many applications.

Mots-clés : computing methodologies computational photography comp  methodologies 3d imaging,comp  methodologies image representations comp  methodologies ray tracing comp,methodologies reflectance modeling
Projet ERC : enzC-Hem (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Manchester — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1492424.0 €

The availability of a versatile catalytic platform to precisely target and functionalize individual C-H bonds in complex organic molecules would revolutionize our synthetic strategies, leading to streamlined routes to high value chemicals and supporting the development of a ‘greener’ chemical industry. Although an impressive range of C-H functionalizations can be achieved with small transition metal complexes, site selectivity is often determined by features of the substrate, and not by the catalyst. A general approach to achieve the more aspirational ‘catalyst controlled’ transformations requires molecular recognition elements within the catalyst which: a) allow precise substrate orientation and b) can be tuned to alter selectivity. In principle, these requirements could be perfectly addressed by protein catalysts which can be readily adapted via laboratory evolution. However, enzyme engineering strategies are currently limited to Nature’s twenty amino acid alphabet, severely limiting the range of metal co-ordination environments, and thus catalytic activities, that are accessible within proteins. In enzC-Hem, I will exploit advanced protein engineering technology available in my laboratory to install ‘chemically programmed’ ligands and/or noble metal co-factors into selected enzyme scaffolds. I will show that the resulting C-H activation catalysts can be systematically optimized via directed evolution with an expanded genetic code using modern ultra-high throughput methods (>100 variants per second), yielding biocatalysts with augmented selectivity/activity profiles. Thus my approach merges the broad range of C-H functionalizations accessible with small molecule catalysts with precise control of selectivity provided by proteins. The biocatalysts developed will address major global challenges in biotechnology and synthetic chemistry, from enhancing lignocellulose derived biofuel production to revealing novel bioactive molecules via late-stage functionalizations.

Mots-clés : biocatalysis,c h activation,enzyme engineering and evolution
Projet ERC : EMAGIN2D (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Valencia — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UV
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

The avenue of magnetism in the field of 2D materials has marked the ultimate milestone in the discovery of one-atom-thick classes of materials. Bulk ferromagnets and antiferomagnets now have their 2D counterparts and are at one’s provision for the realization of imagination-limited artificial layered structures. At the same time, this awaited breakthrough has brought in new conundrums that demand investigation. This project is driven by the exploration of the limits of van der Waals 2D magnets from both a fundamental physics and a materials science and devices point of view. Firstly, it addresses fundamental key questions regarding spin order at the true 2D limit, which remain a mystery to the date. Here, the great variety of magnetic anisotropies exhibited by the transition metal halides will shed new light to the subtle equilibrium of interactions in few-layer magnets. Secondly, the project will invoke the control of the magnetic ground states and spin textures in true 2D magnets via electrical manipulation. Electric fields will assist in tuning the magnetic coupling and critical behaviour and the spatial manipulation of spin topologies. Anticipated breakthroughs will be the enhancement of the critical temperature in semiconducting single layer magnets towards room temperature 2D magnetism and the realization of single-layer multiferroic 2D materials. Thirdly, the field effect electrical control of magnetism in designer van der Waals and lateral heterostructures will allow for an enhanced magneto-electric coupling, yielding functional devices for effective charge-to-spin transduction that hold promise in spintronics. The proposal will achieve success by an integral approach to research, through the combination of the study of solid-state growth techniques together with the implementation of state-of-the-art deterministic manipulation of 2D materials in inert conditions and the use high resolution magnetism probes to test hybrid magnetic-optoelectronic devices.

Mots-clés : multiferroics,2d materials