Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PROWAT (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Dutch Research Council — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : NWO
Type d'entité : Recherche
Financement ERC de l'entité : 2495000.0 €

In recent years water near surfaces and solutes has been observed to be differently structured and to show slower reorientation and hydrogen-bond dynamics than in bulk. Aqueous proton transfer is a process that strongly relies on the structure and dynamics of the hydrogen-bond network of liquid water and that often occurs near surfaces. Examples are thylakoid and mitochondrial membranes and the nanochannels of transmembrane proteins and fuel cells. An important but experimentally largely unexplored area of research is how the rate and mechanism of aqueous proton transfer change due to the surface-induced structuring of the water medium. Theoretical work showed that the structuring and nano-confinement of water can have a strong effect on the proton mobility. Recently, experimental tech- niques have been developed that are capable of probing the structural dynamics of water molecules and proton-hydration structures near surfaces. These techniques include heterodyne detected sum-frequency generation (HD-SFG) and two-dimensional HD-SFG (2D-HD-VSFG). I propose to use these and other advanced spectroscopic techniques to study the rate and molecular mech- anisms of proton transfer through structured aqueous media. These systems include aqueous solutions of different solutes, water near extended surfaces like graphene and electrically switchable monolayers, and the aqueous nanochannels of metal-organic frameworks. These studies will provide a fundamen- tal understanding of the molecular mechanisms of aqueous proton transfer in natural and man-made (bio)molecular systems, and can lead to the development of new proton-conducting membranes and nanochannels with applications in fuel cells. The obtained knowledge can also lead to new strategies to control proton mobility, e.g. by electrical switching of the properties of the water network at surfaces and in nanochannels, i.e. to field-effect proton transistors.
Projet ERC : MICROSCOPE (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 1495161.0 €

In recent years, archaeogenetic studies have yielded striking insights into European prehistory from ancient DNA. However, these studies focus on times prior and up to the Bronze Age, whereas more recent periods are still poorly covered. A key challenge with studying more recent time periods is the homogenisation of European populations since the late Neolithic, which exposes the limits of many existing analytical methods that try to detect population movements. To overcome these limits, in this proposal I will develop a genetic 'microscope', a new set of fine-scaled analytical methods based on rare genetic variation, which will allow us to analyse ancient genomic data to infer population structure with unprecedented detail. With this new toolbox, I will undertake the largest archaeogenetic investigation of the pre-Roman European Iron Age to date. A specific focus will be the ‘Celtic’ world, encompassing a core region spanning from parts of France into Slovakia, and which reached its maximum extent in the third century BC, spanning from the Iberian Peninsula to Anatolia. I will collaborate with a large number of partners from archaeology and anthropology, as well as genetic laboratories, to sample and analyse 600 skeletal remains from this region and time period. Using the new methods, I aim to investigate i) population structure during the early Iron Age in the 'Celtic' core region of Western and Central Europe; ii) the genetic evidence for the so-called 'Celtic migrations' from the third century BC, specifically by analysing samples from the Iberian Peninsula, Northern Italy, Hungary/Romania and the British isles; iii) how migration and population admixture are reflected at the community- and family level by ‘zooming in’ into selected archaeological sites to reconstruct family pedigrees. With new methodology, new reference data, and hundreds of ancient genomes from the pre-Roman Iron Age, this project will set new standards for archaeogenetic studies in Europe.

Mots-clés : archaeogenetics,population history
Projet ERC : DarkGRA (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Sapienza University of Rome — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1337480.94 €

In recent years, our theoretical understanding of the strong-field regime of gravity has grown in parallel with the observational confirmations that culminated in the landmark detection of gravitational waves (GWs). This synergy of breakthroughs at the observational, technical, and conceptual level offers the unprecedented opportunity to merge traditionally disjoint areas, and to make strong gravity a precision tool to probe fundamental physics. The aim of the DarkGRA project is to investigate novel effects related to strong gravitational sources -such as black holes (BHs) and compact stars- that can be used to turn these objects into cosmic labs, where matter in extreme conditions, particle physics, and the very foundations of Einstein's theory of gravity can be put to the test. In this context, we propose to explore some outstanding, cross-cutting problems in fundamental physics: the existence of extra light fields, the limits of classical gravity, the nature of BHs and of spacetime singularities, and the effects of dark matter near compact objects. Our ultimate goal is to probe fundamental physics in the most extreme gravitational settings and to devise new approaches for detection, complementary to laboratory searches. This groundbreaking research program -located at the interface between particle physics, astrophysics and gravitation- is now made possible by novel techniques to scrutinize astrophysical compact objects, by current and future GW and X-ray detectors, and by the astonishing precision of pulsar timing. If supported by a solid theoretical framework, these new observations can potentially lead to surprising discoveries and paradigm shifts in our understanding of the fundamental laws of nature at all scales.

Mots-clés : black holes,gravitational waves,event horizon,spacetime,singularity,superradiance,neutron stars,dark matter,pulsars
Projet ERC : ERC-EuropePMC-2-2014 (Horizon 2020, appel 2014, Low value grant)
Entité participante : European Molecular Biology Laboratory — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : EMBL
Type d'entité : Recherche
Financement ERC de l'entité : 60000.0 €

In support of the ERC open access strategy, it is critical for the ERC to identify published scientific articles that have been based on its funding schemes, in order to assess the impact of the research supported. Currently, the relationship between funding source and article is made only sporadically, years later in end-of-grant reports, or lost altogether, as there is no structured method for recording these associations. Ideally, the funding source should be identified as part of journal manuscript submission processes, however, this idea is currently in its very early stages and will not address the backlog of articles already published. Therefore, we propose to use text-mining methods to identify funding statements in full text articles available in Europe PubMed Central as an accurate and cost-effective solution to linking articles to funding sources. We will assess the outcomes through standard text-mining quality-assessment methods as well as through consultation with ERCEA staff. Anticipating useful outcomes, we will use the methods developed to identify ERC-funded articles in Europe PubMed Central on a routine basis, and make those results available in the search and article browse features on the Europe PubMed Central website. Finally, we will explore the feasibility of extending the approach to other Europe PubMed Central funders.

Mots-clés : text mining,europe pmc,erc grants,grant attribution statements,full text,open access
Projet ERC : COSMOS (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Université Catholique de Louvain — Pays : Belgique — Rôle : Partner
Acronyme de l'entité : UCL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 68750.0 €

In survival analysis investigators are interested in modeling and analysing the time until an event happens. It often happens that the available data are right censored, which means that only a lower bound of the time of interest is observed. This feature complicates substantially the statistical analysis of this kind of data. The aim of this project is to solve a number of open problems related to time-to-event data, that would represent a major step forward in the area of survival analysis. The project has three objectives: [1] Cure models take into account that a certain fraction of the subjects under study will never experience the event of interest. Because of the complex nature of these models, many problems are still open and rigorous theory is rather scarce in this area. Our goal is to fill this gap, which will be a challenging but important task. [2] Copulas are nowadays widespread in many areas in statistics. However, they can contribute more substantially to resolving a number of the outstanding issues in survival analysis, such as in quantile regression and dependent censoring. Finding answers to these open questions, would open up new horizons for a wide variety of problems. [3] We wish to develop new methods for doing correct inference in some of the common models in survival analysis in the presence of endogeneity or measurement errors. The present methodology has serious shortcomings, and we would like to propose, develop and validate new methods, that would be a major breakthrough if successful. The above objectives will be achieved by using mostly semiparametric models. The development of mathematical properties under these models is often a challenging task, as complex tools from the theory on empirical processes and semiparametric efficiency are required. The project will therefore require an innovative combination of highly complex mathematical skills and cutting edge results from modern theory for semiparametric models.

Mots-clés : survival analysis,cure models,copulas,quantile regression,dependent censoring,measurement errors,endogeneity,asymptotic theory,semiparametric inference
Projet ERC : DA QC (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1929552.0 €

In the 1970s, researchers started to utilize quantum mechanics to address questions in computer science and information theory— establishing new research directions such as quantum computing. Now, more than four decades later, we are at the dawn of a new "computing age" in which quantum computers indeed will find its way into practical application. However, while impressive accomplishments can be observed in the physical realization of quantum computers, the development of automated tools and methods that provide assistance in the design and realization of applications for those devices is at risk of not being able to keep up with this development anymore—leaving a situation where we might have powerful quantum computers but hardly any proper means to actually use them. This project aims to provide a solution for this upcoming design gap by developing efficient and practical relevant methods for corresponding simulation, synthesis, and verification tasks. While the current state of the art severely suffers from the interdisciplinarity of quantum computing (leading to the consideration of inappropriate models, inconsistent interpretations, or "wrong" problem formulations), this project will build a bridge between the design automation community and the quantum computing community. This will allow to fully exploit the potential of design automation which is hardly utilized in quantum computing yet. Since quantum computers are reaching feasibility, the methods developed within this project will be highly demanded. Preliminary investigations conducted in preparation of this proposal already showed the potential of such an endeavor and raised significant attention in the quantum computing community and its "big players". The project plans to continue these developments on a larger scale—eventually providing the foundation for design automation methods that accomplish for quantum computing what the design automation community realized for classical electronic circuits.

Mots-clés : design automation,quantum computing,quantum circuit simulation,compilation,synthesis,verification,equivalence checking,decision diagrams,data structures,reasoning engines,search algorithms
Projet ERC : CATACOAT (Horizon 2020, appel 2017, 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 : 1785195.0 €

In the CATACOAT project, we will develop layer-by-layer solution-processed catalyst overcoating methods, which will result in catalysts that have both targeted and broad impacts. We will produce highly active, stable and selective catalysts for the upgrading of lignin – the largest natural source of aromatic chemicals – into commodity chemicals, which will have an important targeted impact. The broader impact of our work will lie in the production of catalytic materials with unprecedented control over the active site architecture. There is an urgent need to provide these cheap, stable, selective, and highly active catalysts for renewable molecule production. Thanks to its availability and relatively low cost, lignocellulosic biomass is an attractive source of renewable carbon. However, unlike petroleum, biomass-derived molecules are highly oxygenated, and often produced in dilute-aqueous streams. Heterogeneous catalysts – the workhorses of the petrochemical industry – are sensitive to water and contain many metals that easily sinter and leach in liquid-phase conditions. The production of renewable chemicals from biomass, especially valuable aromatics, often requires expensive platinum group metals and suffers from low selectivity. Catalyst overcoating presents a potential solution to this problem. Recent breakthroughs using catalyst overcoating with atomic layer deposition (ALD) showed that base metal catalysts can be stabilized against sintering and leaching in liquid phase conditions. However, ALD creates dramatic drops in activity due to excessive coverage, and forms an overcoat that cannot be tuned. Our materials will feature the controlled placement of metal sites (including single atoms), several oxide sites, and even molecular imprints with sub-nanometer precision within highly accessible nanocavities. We anticipate that such materials will create unprecedented opportunities for reducing cost and increasing sustainability in the chemical industry and beyond.

Mots-clés : heterogeneous catalysis,biomass conversion,lignin
Projet ERC : QUMIN (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : University of Cambridge — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2399381.99 €

In the QUMIN proposal we will build on recent developments in spintronics, circuit quantum electrodynamics and superconducting quantum computing in order to advance the fledgling research field of quantum magnonics. We will employ micro-scale magnonic resonators fabricated from YIG thin films and planar superconducting microwave resonators and superconducting transmon qubits. The combination of these basic elements will enable us to create hybrid magnon/photon and magnon/qubit quantum states and probe and control their joint coherence. An end goal of the project is to controllably entangle a superconducting qubit and a magnet. The concept of circuit quantum electrodynamics, developed in superconducting quantum computing, has enabled strong light-matter coupling at microwave frequencies and has been one of the driving forces behind the advances in quantum computing. Over the same time frame there has been an intense development of microwave spintronics partly motivated by the discovery of spin-transfer torque and spin pumping. Most recently, motivated by its exceptional magnetic properties, there has been a renaissance of research in magnetic insulator YIG. Initial experiments show strong coupling between electromagnetic resonators and magnetic resonators. But this is just the start and a wide variety of increasingly sophisticated experiments are to follow. An important aspect of our proposal is to use the non-uniform modes of micro-scale magnonic resonators, enabling experiments close to or at zero magnetic field to ensure compatibility with superconducting qubits. Furthermore we place an emphasis on the use of microwave spintronic techniques, using the spin-Hall effect in order to control and measure the magnonic resonator. As well as exploring this new quantum magnonics avenue, our proposal will further understanding into the room-temperature magnetic phenomena that make YIG an essential material for microwave electronics.
Projet ERC : QuAnGIS (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Utrecht University — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499412.0 €

In the age of big data, geographic information has become a central means for data scientists of various disciplines to embed their analysis into a spatio-temporal context, from human mobility patterns and social inequality to the investigation of personal health. However, as the variety of data sources available on the Web increases, it becomes more and more impossible to comprehend and utilize all tools available to answer geo-analytical questions. The variety of formats and syntaxes required by Geographic Information System (GIS) toolboxes or statistical packages divides the research community into various tool expert groups. Hence, whenever a functionality is needed but not available in one tool, analysts are forced to reformulate their questions in terms of the technicalities of another tool. Furthermore, new tools are difficult to learn, and translations cause severe interoperability problems. Finally, this procedure does not scale with the increasing variety of analytic resources on the Web, preventing analysts from tapping its full potential, and making the promise of seamless big data analytics a mere distant dream. Consider, in contrast, how easy it is for a user of a digital smartphone assistant such as Amazon's Alexa to ask a question like "What is the weather today?" and get back an answer from the Web. It would mean a tremendous breakthrough in information science if analysts could similarly ask familiar questions in order to get the tools and data required to answer them. Unfortunately, analytic technology currently cannot handle such questions. To realize this vision, it is necessary to understand how analytic resources can be captured with the questions they answer. In this project, I will develop a novel theory of interrogative spatial concepts to turn geo-analytical questions into a machine-readable form using semantic queries. In this form, questions can directly be matched with the capacity of major analytic GIS tools and data on the Web.

Mots-clés : geographic information system,retrieval of geoanalytic resources,semantic web
Projet ERC : PersoNews (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1479515.0 €

In the digital media environment, user attention is scarce and competition for ‘eyeballs’ is fierce. Profiling and targeting readers with customised news and advertisements that match their individual interests is widely seen as a solution. The personalization of news media content enables new financing strategies and means to capture the audience’s attention. But personalisation is also part of a more fundamental paradigm shift in the media’s role from public interest intermediary to personal information coach. This research will answer critical questions about the implications for individual users and contribute to a new normative theory of the role of personalised media in a democratic society. To do so, this project integrates legal research, communication sciences and political sciences, undertakes comparative, normative and evidence-based research, and carries out experiments, interviews and a survey. Two communication science postdocs will conduct empirical research into user concerns, the conditions that affect users’ acceptance of media personalisation (postdoc 1), and how personalisation affects journalistic practices and ethics (postdoc 2). Informed by these insights, two PhD students will scrutinise the legal framework and answer important questions about the legal protection of the public’s trust in editorial integrity (PhD 1) and autonomous, non-discriminatory information access (PhD 2). The PI will develop a normative framework of personalised media, based on the empirical research and political theories about the democratic role of the media. This responds to the criticism that existing theories are increasingly disconnected from the realities of digital media and their distinct contribution to democratic and participatory processes. The project will explore the potential of personalisation to expose citizens to more relevant or diverse content, thus reversing widespread concerns about information overload, filter bubbles and selective exposure.

Mots-clés : personalised news,profiling and targeting,big data,user concerns,regulation,normative theory,public information policy,democratic role media,multi disciplinary,evidence based,comparative