Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : FORWARD (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
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 : 1965045.0 €

To detect or generate complex light beams that are increasingly needed in biology and photonics (light with non-zero angular momentum and non-classical light), it is necessary to rely on bulky and sophisticated setups, considerably limiting their potential. The FORWARD project aims at obtaining the same functionalities with a new generation of optoelectronic components of submicron thickness in the near infrared range. This ambitious objective implies to devise radically new ways of creating and manipulating complex light at the nanoscale. In FORWARD, this tremendous challenge will be addressed by hybridizing two classes of artificial media-colloidal quantum dots (CQDs) and metamaterials-and leveraging advanced cooperative behaviours within the hybrids. In the new devices, which will be pumped electrically, the active layers will be made of a film of CQDs interwoven with the metallic inclusions of an optical metamaterial. FORWARD has a strong multidisciplinary character as it lies at the crossroads of nanocrystal processing, nanofabrication, nanophotonics, condensed matter physics and optoelectronics. First, we will hybridize metallic metamaterials and CQDs, study the transport properties in these devices and develop metamaterial/CQD photodetectors demonstrating the advantage of the hybridization. Second, we will induce classical cooperative effects between the different metamaterial inclusions and utilize this approach to fabricate hybrids LEDs capable of emitting optical vortices. Last, we will induce quantum synchronizations among the CQDs and demonstrate hybrids LEDs that produce coherent and non-classical light. Each demonstrator of the project will be a world first in terms of functionalities, miniaturization and operation principle. Besides, this initiative can be seen as the first of its kind that takes a unified and multidisciplinary view at artificial media, opening new horizons for synthetic composite materials in optics, electronics and optoelectronics.

Mots-clés : colloidal quantum dots,metamaterials
Projet ERC : EvoGenMed (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : University of Bath — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2260496.0 €

To make for better diagnostics and safer applications of genomics we need a better understanding of our genome and how it functions. Until recently we thought we knew: intergenic sequence must be largely “junk” and mutations that, for example, affect genes but not the protein (synonymous mutations) must be effectively neutral. This degenerate genome view accords with the nearly-neutral theory’s prediction that selection will be weaker when populations are small. But is this all there is to it? I shall investigate two new interrelated perspectives on genome evolution. First, I suggest that to mitigate errors, owing to our high error rates, our genome can be under stronger, not weaker, selection. Second, that errors might be a source of evolutionary novelty. Error mitigation, my team has shown, often involves selection on seemingly innocuous mutations such as synonymous changes. Remarkably, we discovered that selection to ensure error-proof splicing is possibly more prevalent on synonymous mutations when populations are small, making seemingly innocuous mutations stronger candidates for human diseases. I shall provide the first test of the new error-proofing perspective through comparative genomic analysis on synonymous site evolution. To investigate error as a source of novelty I shall consider whether expression piggy-backing (expression of a gene affecting its neighbors) forces rewiring of gene networks. Importantly, I shall translate our new understanding to enable better diagnostics and improved therapeutics. I shall develop a much-needed computer package to identify candidate disease-causing synonymous changes. In addition, knowing how synonymous sites modulate splicing will allow me to design better intronless transgenes. Transgenes must also be inserted in genomic regions immune to piggy-backing. I will examine transposable element related piggy-backing to characterize “safe” sites for therapeutic gene insertion and mammalian transgenesis more generally.

Mots-clés : synonymous mutations,expression piggy backing,transgenes,nearly neutral theory,error mitigation
Projet ERC : STRATIFY (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Charité - Universitätsmedizin Berlin — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 988895.34 €

To reduce the burden of mental disorders it is a formidable aim to identify widely applicable disease markers based on neural processes, which predict psychopathology and allow for targeted interventions. We will generate a neurobehavioural framework for stratification of psychopathology by characterising links between network properties of brain function and structure and reinforcement–related behaviours, which are fundamental components of some of the most prevalent mental disorders, major depression, alcohol use disorder and ADHD. We will assess if network configurations define subtypes within and if they correspond to comorbidity across these diagnoses. We will identify discriminative data modalities and characterize predictors of future psychopathology. To identify specific neurobehavioural clusters we will carry out precision phenotyping of 900 patients with major depression, ADHD and alcohol use disorders and 300 controls, which we will investigate with innovative deep machine learning methods derived from artifical intelligence research. Development of these methods will optimize exploitation of a wide range of assessment modalities, including functional and structural neuroimaging, cognitive, emotional as well as environmental measures. The neurobehavioural clusters resulting from this analysis will be validated in a longitudinal population-based imaging genomics cohort, the IMAGEN sample of over 2000 participants spanning the period from adolescence to adulthood and integrated with information generated from genomic and imaging-genomic meta-analyses of >300.000 individuals. By targeting specific neural processes the resulting stratification markers will serve as paradigmatic examples for a diagnostic classification, which is based upon quantifiable neurobiological measures, thus enabling targetted early intervention, identification of novel pharmaceutical targets and the establishment of neurobehaviourally informed endpoints for clinical trials.
Projet ERC : STRATIFY (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of Southampton — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 293919.01 €

To reduce the burden of mental disorders it is a formidable aim to identify widely applicable disease markers based on neural processes, which predict psychopathology and allow for targeted interventions. We will generate a neurobehavioural framework for stratification of psychopathology by characterising links between network properties of brain function and structure and reinforcement–related behaviours, which are fundamental components of some of the most prevalent mental disorders, major depression, alcohol use disorder and ADHD. We will assess if network configurations define subtypes within and if they correspond to comorbidity across these diagnoses. We will identify discriminative data modalities and characterize predictors of future psychopathology. To identify specific neurobehavioural clusters we will carry out precision phenotyping of 900 patients with major depression, ADHD and alcohol use disorders and 300 controls, which we will investigate with innovative deep machine learning methods derived from artifical intelligence research. Development of these methods will optimize exploitation of a wide range of assessment modalities, including functional and structural neuroimaging, cognitive, emotional as well as environmental measures. The neurobehavioural clusters resulting from this analysis will be validated in a longitudinal population-based imaging genomics cohort, the IMAGEN sample of over 2000 participants spanning the period from adolescence to adulthood and integrated with information generated from genomic and imaging-genomic meta-analyses of >300.000 individuals. By targeting specific neural processes the resulting stratification markers will serve as paradigmatic examples for a diagnostic classification, which is based upon quantifiable neurobiological measures, thus enabling targetted early intervention, identification of novel pharmaceutical targets and the establishment of neurobehaviourally informed endpoints for clinical trials.
Projet ERC : NVS (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Bar-Ilan University — Pays : Israël — Rôle : PI
Acronyme de l'entité : BIU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2772553.0 €

To understand how the brain works, tools need to be developed that will allow neuroscientists to investigate how interactions between individual neurons lead to emergent networks. Towards this goal, we will develop targetable voltage sensing nanorods that self-insert into the cell membrane and optically and non-invasively record action potentials at the single particle and nanoscale level, at multiple sites and across a large field-of-view. In semiconductors, absorption and emission band edges are modulated by an external electric field, even more so when optically excited electron-hole pairs are confined, giving rise to the quantum confined Stark effect. The physical origin of this effect is in the separation of photoexcited charges, creating a dipole that opposes the external field. The proposed sensors will optically record action potential with unique advantages not offered by other methods: much larger voltage sensitivity, high brightness, and hence single-particle voltage sensitivity, large spectral shift (affording noise-immune ratiometric measurements), fast temporal response, minimal photobleaching, large Stokes shifts, large two-photon excitation cross sections, excellent performance in the NIR, and compatibility with lifetime imaging. The proposed sensors could afford, for example, the recording of pre- and post-synaptic membrane potentials, sub-threshold events, ultrafast spiking, individual ion channel activity, or a release of ions from single Ca+2 stores. In addition, deep tissue imaging could be afforded by two photon microscopy and far-field non-linear temporal focusing combined with lifetime imaging. Here we seek to optimize all aspects of the sensors’ synthesis, functionalization, delivery, targeting and detection, in order to provide neuroscientists and physiologists a viable and user-friendly technology that will be generally useful for the study of action potential signals in the brain and in healthy or diseased heart and muscle tissues.

Mots-clés : biophysics,electrophysiology,neurobiology,single molecule spectroscopy,physical chemistry,analytical chemistry,method development in chemistry,physical chemistry of biological systems
Projet ERC : macroevolution.abc (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : University of Oslo — Pays : Norvège — Rôle : PI
Acronyme de l'entité : UiO
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1990213.0 €

To what degree do microevolutionary processes that happen on a generational time scale matter for macroevolutionary patterns recorded on time scales of millions of years in the fossil record? To answer this fundamental question in evolutionary biology, we need a model system in which we can overcome the conceptual and empirical boundaries imposed by disparate timescales. macroevolution.abc will develop bryozoans as the Drosophila of macroevolution, integrating molecular, fossil, phenotypic, ecological and environmental data to shed light on the currently inaccessible “Dark Time Scale” (thousands, to tens of thousands of years), spanning the chasm between microevolution studied by population geneticists and evolutionary ecologists and macroevolution studied by paleontologists and comparative phylogeneticists. Using bryozoans, a little-known but uniquely ideal study group for evolutionary questions, I will generate, then cross-integrate, (i) empirical time series of intra- and interspecific biotic interactions; (ii) phenotypic data describing variation within genetic individuals, variation among contemporaneous individuals in both extinct and living populations; (iii) robust estimates of abundance shifts in fossil populations; and (iv) speciation and extinction rate estimates from molecular phylogenies and the fossil record. The new bryozoan model evolutionary system will provide answers to previously intractable questions such as “do ecological interactions crucial for individual survival matter for group diversification patterns observed on geological time scales” and “why do we have to wait a million years for bursts of phenotypic change”?

Mots-clés : macroevolution,paleobiology,marine invertebrates
Projet ERC : EXCHANGE (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Coimbra — Pays : Portugal — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 486002.12 €

Today we are living in the “genetic age” of criminal investigation. There is a widespread cultural belief that DNA technology has the unrivalled capacity to identify authors of crimes. In light of this ideology, EU Law (Prüm Decision, 2008) obliges all Member States to create the conditions for the reciprocal automated searching and comparison of information on DNA data for the purpose of combating cross-border crime, terrorism and illegal immigration. Forensic geneticists play a crucial role in this scenario: they develop the techno-scientific procedures that enable DNA data to be shared across national boundaries. EXCHANGE aims to understand the close links between a highly specialised field of expert knowledge – forensic genetics – and surveillance in the EU. If the EU succeeds in this political project, about 10 million genetic profiles of identified individuals will be exchanged between agencies in all EU countries. This raises acute cultural, political and societal challenges. EXCHANGE aims to address these challenges by scrutinizing how forensic geneticists, within the context of the transnational exchange of DNA data in the EU, engage with the social values attributed to science – i.e. objectivity, truth – and the values of social control, citizenship and democracy. The expected outputs are: 1. To provide a general picture of the Prüm framework by conducting interviews with forensic geneticists in all EU countries; 2. To develop in-depth knowledge of forensic geneticists’ activities relating to Prüm using ethnographic observation and qualitative analysis of criminal cases; 3. To study countries with different local positionings in relation to Prüm by means of a comparative study involving Portugal, Germany, the Netherlands and the UK. EXCHANGE stimulates interdisciplinary dialogue between the social sciences and the forensic genetics. This research also tackles questions that are relevant to all the actors involved in criminal justice cooperation in the EU.

Mots-clés : social studies of forensic genetics,dna evidence,transnational exchange of dna data,surveillance,suspects,social control,citizenship and human rights,democracy,pr m decision
Projet ERC : CUSTOMER (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Uppsala University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499894.0 €

Today, many industrial products are defined by software and therefore customizable: their functionalities implemented by software can be modified and extended by dynamic software updates on demand. This trend towards customizable products is rapidly expanding into all domains of IT, including Embedded Real-Time Systems (ERTS) deployed in Cyber-Physical Systems such as cars, medical devices etc. However, the current state-of-practice in safety-critical systems allows hardly any modifications once they are put in operation. The lack of techniques to preserve crucial safety conditions for customizable systems severely restricts the benefits of advances in software-defined systems engineering. CUSTOMER is to provide the missing paradigm and technology for building and updating ERTS after deployment – subject to stringent timing constraints, dynamic workloads, and limited resources on complex platforms. CUSTOMER explores research areas crossing two fields: Real-Time Computing and Formal Verification to develop the key techniques enabling (1) dynamic updates of ERTS in the field, (2) incremental updates over the products life time and (3) safe updates by verification to avoid updates that may compromise system safety. CUSTOMER will develop a unified model-based framework supported with tools for the design, modelling, verification, deployment and update of ERTS, aiming at advancing the research fields by establishing the missing scientific foundation for multiprocessor real-time computing and providing the next generation of design tools with significantly enhanced capability and scalability increased by orders of magnitude compared with state-of-the-art tools e.g. UPPAAL.

Mots-clés : real time systems,embedded systems,safety critical systems,scheduling,modelling and verification
Projet ERC : ELECTROFLUID (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Leibniz Association — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LG
Type d'entité : Recherche
Financement ERC de l'entité : 1499375.0 €

Today, most electronics and robots are based on solid metals and semiconductors. This project aims at “Electrofluids” that conduct electrons while flowing as liquids. Because liquids have virtually no yield strength, they are ideal materials to replace solid metal leads in truly soft devices. ELECTROFLUID uses highly concentrated suspensions that are liquid in a wide temperature range. Transient conductive networks in suspended particles of commonly used conductors provide high level of electronic conductivity at the viscosities required for soft electronics and robots. They contain common conductive materials such as carbon, silver, gold, and copper and do not require specialized low-melting alloys of gallium or other expensive elements. In order to create stable Electrofluids with large conductivity at low viscosity with tuneable rheology, I study the interplay between particle-particle friction, contact resistance, percolation, bulk resistance, and suspension viscosity. I use both custom-synthesized and commercial particles in a size range of tens of nanometres to few microns and with different shapes, modify their surfaces with conventional and pi-conjugated surfactants, and formulate concentrated suspensions that exhibit large conductivity at low viscosity. The combination of different particle sizes, shapes, and fluids enables tuning the properties of the fluid towards specific application cases, for example to create highly flexible leads for logic signals versus high-power connections for the connection of actuators. The fluids will be encapsulated in elastomer tubes or micropatterned surfaces as they are commonly used in stretchable electronics. The specific aims of the project are: (i) to design highly concentrated suspensions that form transient percolating networks, (ii) to use this knowledge and synthesize fluids with tuneable electrical conductivity at low viscosity, (iii) to demonstrate that Electrofluids can be curtailed for particular applications.

Mots-clés : electronically conductive liquids,highly concentrated suspensions,soft electronics,conductive particles,transient conductive networks,complex fluids,percolation
Projet ERC : PSOTI (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Technical University of Darmstadt — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499775.0 €

Today, when using services on the Internet, users have to fully entrust a single service provider with their data. Many of these service providers are located outside the EU and there are cases where data has not only been leaked by attacks of outsiders or insiders, but also by governments who built backdoors into software or hardware, or forced service providers to give out sensitive user data. With the new EU General Data Protection Regulation (GDPR) also companies have an obligation to properly protect users’ data. My project PSOTI will eliminate the need to trust a single service provider and empower users to freely control their data. For this, the users can choose a subset of multiple service providers that they are willing to trust who jointly process their data and privacy is guaranteed even if all but one are compromised. The main goal of PSOTI is to develop privacy-preserving services for commonly used tasks on the Internet that are feature-rich and efficient enough for practical use. This will allow to privately store, retrieve, search, and process data, and help to comply with the GDPR and preserve the fundamental rights to privacy and the protection of personal data. As underlying technology, we will build a real-world secure multi-party computation (MPC) framework that can also be used for other large-scale privacy-preserving applications such as genomics or machine learning. To achieve our main goal, we will solve the following challenges: 1) Develop private query protocols on outsourced data that process complex queries such as Boolean formulas over string matches or range queries, and even hide the query’s structure. 2) Build a real-world MPC framework that scales to large functionalities, is highly parallelized, interoperable, and fully integrated. 3) Demonstrate real-world applicability for privacy-preserving and feature-rich services on the Internet such as file storage (going beyond Dropbox), surveys (going beyond Google Forms), and email.

Mots-clés : privacy enhancing technologies,secure computation