Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : Work-STeP (Horizon 2020, appel 2017, Proof of concept grants)
Entité participante : Utrecht University — Pays : Pays-Bas — Rôle : Partner
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 12268.75 €

With the proposed Workforce Sustainability Testing Platform (Work-STeP) organisations will have a tool to assess their HR practices with regards to workforce sustainability (e.g. engagement, health, performance).The proposed project will have a profound impact on the European business community. By automating all aspects of the platform, Work-STeP is able to offer its services at affordable rates. Where traditional HR analytics are often too costly for small and medium establishments (SMEs), with Work-STeP SMEs too will be able to assess their workforce sustainability. The project will be embedded in the host institution’s Future of Work Hub and will be supported by its advisory committee consisting of executives from large national and international organisations. The advisory committee, and the PI’s network of organisations from the Sustainable Workforce project will ensure that Work-STeP will be in line with industry demands. In the Proof of Concept phase the team will determine whether and to what extent the platform can use our substantial benchmark dataset from the ERC-Advanced Sustainable Workforce project, in which we investigated what HR investments organisations make and the effects they have on the workforce, in 259 organisations from nine EU countries across six economic sectors. Work-STeP will offer the manager insight in key performance measures of teams within the organisation. Lower team or organisation scores, in comparison with their sector and region, expose areas where there is room for growth in terms of workforce sustainability. These areas of concern, team demographics and the Sustainable Workforce analyses on policy effectiveness allow Work-STeP to offer organisations contextualized advice on which investments to use.

Mots-clés : workforce sustainability,hr policy assessment,online testing platform
Projet ERC : dataFlow (Horizon 2020, appel 2018, Proof of concept 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 : 149500.0 €

With the recent breakthrough of deep learning methods, we currenty see the advent of employing this methodology in the context of physical simulations. Such simulations are widely used in numerous industrial fields, starting from car and airplane manufacturers, over computer graphics and animations to medical blood flow simulations. The market for computer simulations is currently exceeding 15 billion USD world wide, with rising trends, and 3 billion spent in Europe alone. A significant fraction of these simulations focuses purely on solving various forms of the Navier-Stokes equations. While right now virtually all of these simulations use traditional solvers, we estimate than only a few years from now there will be a significant fraction of deep learning powered solvers. Thus, we are at the right point in time to lay the foundations for commercializing the technology of deep learning for fluid simulations. The goal of this PoC project is to develop a first commercial flow solver based on deep learning that can predict fluid flow solutions almost instantly using a pre-trained model. This project will enable the team of Prof. Thuerey to mature the algorithms developed as part of the ERC Starting Grant \realflow, and turn them into the basis of a marketable product. The initial models will be thoroughly tested and validated, in order to satisfy industrial requirements for reliability and accuracy. In addition, this PoC aims for establishing a platform for flow data collection, interface standards, and trained models. This platform will be developed in conjunction to the deep-learning powered flow solving application, and provide research connections and publicity in parallel to it.

Mots-clés : numerical simulations,machine learning
Projet ERC : REINVENT (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : University of Milano-Bicocca — Pays : Italie — Rôle : PI
Acronyme de l'entité : UNIMIB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

With the start of the second run of the Large Hadron Collider and the discovery of a particle compatible with the Standard Model Higgs boson, the high-energy particle physics community faces the task to carry out precise measurements of the properties of this new particle, in order to establish its nature. At the same time, it will be equally important to keep looking for the yet elusive signs of New Physics. Both tasks rely on the ability to accurately predict the expected signals and to disentangle them from the known backgrounds. At hadronic colliders like the LHC, accurate modeling of the strong interactions is crucial to interpret the experimental outcomes. The goal of this project is to push forward the frontier of precision QCD for event simulations. The key idea is to combine the three possible theoretical description (fixed-order perturbative expansion, resummed calculations and parton showers) into the same theoretical framework, in order to benefit from the advantages of each. The innovative approach proposed here improves over past efforts thanks to the inclusion of higher-logarithmic resummation, which bridges the gap between the perturbative description of hard radiation and the shower domain. This brings together three important advantages: the ability to use the best theoretical description in each region, the sizable reduction of the theoretical uncertainties gained by replacing the shower evolution with the higher-logarithmic resummation, and the ability to produce hadron-level events that can be directly interfaced to detector simulations. By going beyond the state-of-the-art, REINVENT will obtain the most precise theoretical predictions for the LHC in an event generator form that allows for direct comparison to data, producing tools that will be used by both experimentalists and theorists. The technology developed for this project will also have important applications for precision studies at future lepton colliders.

Mots-clés : monte carlo simulations,resummation,higher order qcd corrections
Projet ERC : REINVENT (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : University of Zurich — Pays : Suisse — Rôle : Partner
Acronyme de l'entité : UZH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

With the start of the second run of the Large Hadron Collider and the discovery of a particle compatible with the Standard Model Higgs boson, the high-energy particle physics community faces the task to carry out precise measurements of the properties of this new particle, in order to establish its nature. At the same time, it will be equally important to keep looking for the yet elusive signs of New Physics. Both tasks rely on the ability to accurately predict the expected signals and to disentangle them from the known backgrounds. At hadronic colliders like the LHC, accurate modeling of the strong interactions is crucial to interpret the experimental outcomes. The goal of this project is to push forward the frontier of precision QCD for event simulations. The key idea is to combine the three possible theoretical description (fixed-order perturbative expansion, resummed calculations and parton showers) into the same theoretical framework, in order to benefit from the advantages of each. The innovative approach proposed here improves over past efforts thanks to the inclusion of higher-logarithmic resummation, which bridges the gap between the perturbative description of hard radiation and the shower domain. This brings together three important advantages: the ability to use the best theoretical description in each region, the sizable reduction of the theoretical uncertainties gained by replacing the shower evolution with the higher-logarithmic resummation, and the ability to produce hadron-level events that can be directly interfaced to detector simulations. By going beyond the state-of-the-art, REINVENT will obtain the most precise theoretical predictions for the LHC in an event generator form that allows for direct comparison to data, producing tools that will be used by both experimentalists and theorists. The technology developed for this project will also have important applications for precision studies at future lepton colliders.

Mots-clés : monte carlo simulations,resummation,higher order qcd corrections
Projet ERC : HADES (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Scottish Association For Marine Science — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : SAMS
Type d'entité : Recherche
Financement ERC de l'entité : 109263.86 €

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 : imbh (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe 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 : 1999975.0 €

With this proposed project I will determine whether intermediate-mass black holes (IMBHs) exist. I propose to use ESA's new Gaia mission, the rich Hubble Space Telescope data archive, and state-of-the-art techniques to investigate systems predicted to exist but not yet found hitherto, such as recoiled hyper-compact stellar systems, red-supergiant mass donors to ultra-luminous X-ray sources, and white dwarf tidal disruption events. The latter can only be detected if black holes with masses less than 1E5 Msun are involved. Using these systems and events we can probe the sphere of influence of the IMBH and determine the black hole mass dynamically. Currently, there are strong indications for the existence of IMBHs, but dynamical evidence, the irrefutable proof of their existence, is still lacking. Whereas the unequivocal detection of an IMBH will be a breakthrough discovery in itself, it has also important consequences for searches of dark matter annihilation signals, it will provide a baseline for the rate predictions of gravitational wave radiation events involving IMBHs, and the properties of a population of IMBHs provides important constraints on the growth of supermassive black holes and galaxies. Finally, if we discover IMBHs in hyper-compact star clusters it validates numerical relativity simulations that predict that merging black holes receive a recoil kick. My membership of Gaia's Data Processing and Analysis Consortium gives me a distinct advantage in analysing and interpreting Gaia data that, through the superb angular resolution, immediate spectroscopic observations and all-sky coverage, provides unique capabilities ideally suited for answering the question whether IMBHs exist. My proposed project is the first to recognize the potential of Gaia (WP1&2) as well as the implications of having red supergiant mass donors in some ultra-luminous X-ray sources (WP3) for answering the question on the existence of IMBHs.

Mots-clés : black holes
Projet ERC : ReloCare (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
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 : 1499978.0 €

Within care studies, the transnationalization of care has been mainly understood as drawing on (female) migrant care workers and resulting in a ‘care gap’ in the places such workers leave behind. This project looks at the reverse phenomenon: care relocation, in which the ageing body is relocated to places where care is more affordable. This hotly contested trend, described as ‘grandmother deportation’ or ‘geriatric colonialism’, can be seen as an extreme example of the marketization of care, and entangling welfare states as entitlements are carried across national borders within Europe. This multi-sited anthropological study will take as case studies care homes in Central Eastern Europe (Poland, Czech Republic, Slovakia, and Hungary) that recruit patients from Austria and Germany, and offer care at roughly one-third of the cost of similar institutions in the home countries. What does care relocation do to the people and places involved? Most of these care homes are located in regions characterized by a long German and Habsburg-Hungarian history, adding historical complexity to the story. Some serve only German-speaking patients, others serve local, wealthier elderly people as well. They are run by former migrant care workers and by international companies, bringing labour migration and real estate investment into the picture. ReloCare breaks new ground by encompassing all of these aspects in one study. Alongside in-depth ethnographic studies of daily life in these care homes, the researchers will investigate the nexus of care entrepreneurs and state insurances, and the histories of places and regional migration, providing an understanding of these new transnational entanglements of welfare states. In perceiving care relocation as both part of future making and a response to the privatization of care landscapes in the region, it asks what it means to become old and in need of care in an increasingly intertwined Europe.

Mots-clés : anthropology of care,anthropology of the state,medical anthropology,transnational care landscapes,migration infrastructure,care tourism,political subjectivity,care ethics,care chains,history,human geography,europe
Projet ERC : TARGETSET (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Spanish National Cancer Research Centre — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CNIO
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Within our ERC CoG grant, RSHEALTH, our group has contributed to the to the preclinical development of chemical inhibitors of the ATR kinase as anticancer agents, that are now in clinical trials by several companies. During the course of our investigations, we also made important advances in developing inhibitors of SETD8, another interesting cancer-related target. SETD8 is a histone methyltransferase known to play important roles in DNA replication and repair. Evidence indicating that targeting SETD8 could be interesting for cancer therapy has been building up in recent years. For instance, SETD8 is overexpressed in a wide range of cancers, and recent works identified SETD8 as a specific vulnerability in High-Risk Neuroblastoma or MYC-driven Medulloblastomas. Unfortunately, all available SETD8 inhibitors have low potency and poor pharmacological properties, and none has progressed to the clinic. We here propose to capitalize in our strengths in academic drug development, and our experience in transferring our inhibitors to the industry, in order to facilitate the clinical development SETD8 inhibitors. Our proposal includes objectives that will help us improve the quality of our inhibitors, valorise them in preclinical cancer models and develop companion biomarkers that would be used for patient stratification. All of this would be integrated within a business plan that should facilitate a coherent development of this line of work oriented towards the clinical development of SETD8 inhibitors for the benefit of cancer patients.

Mots-clés : setd8,cancer,drug development,pharmacology,biomarker,preclinical valorisation
Projet ERC : OrgaDetect (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : TU Dresden — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUD
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149687.0 €

Within the ERC Advanced Researcher Grant “NuDev”, promising organic electronic devices especially transistors have been developed. A candidate being able to replace inorganic transistors due its outstanding features and potential low cost production process is the Organic Permeable Base Transistor (OBPT). However, electronic industry is almost completely silicon based today. Therefore, applications using organic electronic devices need to compete on the basis of superior and unique features to outperform inorganic technology. Such a potential application of the OPBT has been achieved in the lab of the PI of the “NuDev” Grant. In a recent scientific breakthrough, a novel organic photodetector technology for the near infrared (NIR) with outstanding features going far beyond the specifications of inorganic detectors has been invented. To fully exploit the advantages of this technology and to achieve integrated devices, organic electronics should be utilized for both amplification and read-out of the detectors. This way, photodetectors as well as fully integrated chip-sized NIR-spectrometers with high detectivity, high resolution, and with all the advantages of organic electronics such as flexibility and low cost mass production are possible. With this Proof-of-Concept Grant, funding is requested for combining OPBTs with the novel photodetector technology of the PI. By achieving optimized prototypes of such a structure, the Proof-of-Concept will be furnished to attract investors to commercialize this result of the NuDev Grant. The multi-billion Euro optical sensor market with its high growth rates on the one hand and the unique features of the PI’s technologies resulting in manifold application fields on the other hand are eminent preconditions for a success of the planned spin-off. Moreover, the described technology is a promising way for Europe to significantly increase its share of the optical sensor market that is currently dominated by Asia and North America.

Mots-clés : organic electronics,organic transistor,photodetector,spectrometer,sensor,optical sensor,thin film electronics,thin film sensor,integrated devices,permeable base transistor
Projet ERC : EXWINGS (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Uppsala University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2456383.0 €

Without stellar winds, life as we know it would not exist. Critical elements like carbon are produced inside luminous cool giant stars, transported to the surface by turbulent gas flows, and ejected into interstellar space by massive outflows of gas and dust. Direct evidence for this scenario comes in the form of dust grains produced in the stellar winds, and detected in meteorites by their isotopic composition. Nevertheless, the current understanding of stellar winds is far from sufficient to draw a realistic, quantitative picture of their effects on stellar evolution and their contribution to the enrichment of the interstellar medium with newly-produced elements and dust. Project EXWINGS aims at a breakthrough in understanding the winds of cool giant and supergiant stars with a novel modeling approach. We will produce global radiation-hydrodynamical ‘star-and-wind-in-a-box’ simulations, based on our recently-developed prototype. For the first time, it will be possible to follow the flow of matter, in full 3D geometry, all the way from the convective, pulsating interior of a cool giant, through its atmosphere and dust-formation zone, into the dust-driven wind region. Extending our unique approach to the warmer, more luminous red supergiants, we will explore alternative driving scenarios for their still enigmatic winds, involving magneto-hydrodynamic waves and radiation pressure on molecules and dust. The current progress in high-angular-resolution instruments, giving resolved views of the stellar atmospheres where the winds originate, presents an excellent opportunity for testing the new models. An ultimate goal is a predictive theory of mass loss and dust production in evolved stars, based on first physical principles. The results of EXWINGS will have a major impact on understanding stellar and galactic chemical evolution, on tracing the origin of building blocks for terrestrial planets, and on constraining physical properties of supernova progenitors.

Mots-clés : agb stars,red supergiants,stellar winds,stellar atmospheres,convection,mass loss,circumstellar matter,radiation hydrodynamics,numerical simulations,high angular resolution techniques,imaging,spectroscopy