Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Fluid-Structure Interaction and Machine Leaning for Controlling Unruptured Intracranial Aneurysms (CURE)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Products and Processes Engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: France
Call: ERC CONSOLIDATOR GRANTS (ERC-2021-COG, 2021)
Start date: 2023-01-01
End date: 2027-12-31
Duration (months): 60.0
Total project cost (EUR): 1891333.0
EU funding (EUR): 1891333.0
Participants: 2
Project status: SIGNED

Developing new capabilities to predict the risk of intracranial aneurysm rupture and to improve treatment outcomes in the follow-up of endovascular repair is of tremendous medical and societal interest, both to support decision-making and assessment of treatment options by medical doctors, and to improve the life quality and expectancy of patients. The proposal aims at identifying and characterizing novel flow-deviator stent devices through a high-fidelity computational framework that combines state-of-the-art numerical methods for fluid-structure interaction modeling (to accurately describe the mechanical exchanges between the blood flow, the surrounding vessel tissue, and the flow-deviator) and deep reinforcement learning algorithms (to identify and to invent a new stent concepts enabling patient-specific treatment via accurate adjustment of the functional parameters in the implanted state). This has never been done before in this context and should thus open both new theoretical and numerical opportunities. CURE takes the vital steps of bringing novel computational and optimization frameworks to the next level capable of studying the selected flow diverter treatment in order to reduce the risk of hemorrhage in cerebral aneurysms, of supporting the decisions of treatment options by medical doctors and finally of providing guidance in the development of new implant design. Such unique capabilities can save millions of lives worldwide, improve the life quality of patients, eliminate lifelong side-effects due to sub-optimal treatment planning and delivery; and reduce the tremendous societal and economic burden linked to poor patient outcome. The proposed work has potential to reshape the future of intracranial aneurysm risk management. It is highly multidisciplinary, and the methods proposed and developed as a part of this research can be quickly adapted to a wide range of engineering and bio-medical applications.

Keywords: unruptured intracranial aneurysms fluid structure interaction computational fluid dynamics machine learning deep reinforcement learning endovascular treatment patient specific stent design
An Odyssey without borders: soil microbiota as drivers of plant species coexistence along successional gradients (BelowGround)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: Netherlands
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2023-06-01
End date: 2026-06-30
Duration (months): 37.0
Total project cost (EUR): 203464.32
EU funding (EUR): 203464.32
Participants: 1
Project status: SIGNED

Our planet is in a biodiversity crisis. To counteract biodiversity loss, the EU’s Biodiversity Strategy for 2030 aims to protect vulnerable ecosystems, reverse ecosystem degradation, and restore biodiversity on agricultural land. However, successful restoration and conservation of plant diversity is hindered by limited understanding of the principles that govern the ability of plant species to coexist and drive plant diversity. My proposed research aims to address the major challenge of restoration and conservation of plant diversity by examining how soil microorganisms contribute to plant species coexistence. My project will draw together fundamental coexistence theory and state-of-the-art knowledge from plant ecology, microbial ecology and soil ecology to reconcile how pathogens and mutualists drive plant coexistence. To develop successful strategies of conservation and restoration of plant diversity it is critical to define a single predictive theory on the role of soil microbes in plant coexistence. I propose to reconcile pathogen- and mutualist-driven coexistence hypotheses into a single framework by addressing two objectives: Along a successional vegetation gradient in which belowground interactions switch from pathogen to mutualist dominated, I will 1) identify which pathogenic and mutualistic microbes plants accumulate with increasing intra-specific density, and 2) determine how these soil microbes influence host plant coexistence. Results will uncover the role of pathogens and mutualists in driving coexistence and whether these different groups of players are mutually exclusive or act simultaneously. This will lay the foundation for urgent tailor-made applied research on the key processes that need conservation and restoration of grassland systems, and uncover the drivers that steer plant community succession towards biodiverse ecosystems.

Keywords: above belowground interactions,plant soil feedback,microbial ecology,coexistence,successional gradient
Training for a Hydrogen Economy based Renewable Energy Society in the Anthropocene (THERESA)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Doctoral Networks
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Spain,Netherlands,Finland
Call: MSCA Doctoral Networks 2021 (HORIZON-MSCA-2021-DN-01, 2021)
Start date: 2022-12-01
End date: 2026-11-30
Duration (months): 48.0
Total project cost (EUR): 1625659.2
EU funding (EUR): 1625659.2
Participants: 7
Project status: SIGNED

Thanks to the long standing collaborations among the Universities of Rovira i Virgili (Spain), Groningen (the Netherlands) and Eastern Finland (Finland), THERESA proposes the first European doctoral programme for legal specialists in the field of the hydrogen economy. In the context of climate emergency and socio-ecological transition of the Anthropocene, Green hydrogen is a promising energy carrier to facilitate the transition to an energy system based on renewable energies. Hydrogen can replace natural gas as a feedstock and help fossil-based economic sectors for which electrification is not possible, or excessively burdensome, to lower their greenhouse gas emissions. Yet, the development of a hydrogen market is characterized by uncertainties and associated economic, societal and environmental risks. The few existing scholarly legal studies on this subject matter highlights the fragmentation of the regulatory framework applying to hydrogen. THERESA combines the focus on three specific themes of regulatory intervention in the hydrogen economy – 1) reducing sectoral fragmentation to spur socio-environmental sustainability; 2) enabling sustainable circular use of hydrogen; and 3) societal engagement in the hydrogen economy – with three methodological approaches – doctrinal constructivism, empirical legal research and legal comparativism – to advance scientific knowledge and form the doctoral experts needed to contribute to the development of a hydrogen economy. THERESA encompasses a fully-fledged training programme offering substantive, theoretical, methodological and transferable skills to the Early State Researchers. THERESA addresses the gender dimension and other diversity aspects not only in the ESRs selection, but also in its theoretical framework.

Keywords: legal specialists,green hydrogen,antropocene
CircularPSP – Public Service Platforms for Circular, Innovative and Resilient Municipalities through PCP (CircularPSP)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Industry
Destination: Increased Autonomy in Key Strategic Value Chains for Resilient Industry
Action type: Pre-Commercial Procurement
Countries involved: Germany,Sweden,Türkiye,Ireland,Slovenia,United Kingdom,Portugal,Belgium,Finland
Call: Boosting green economic recovery and open strategic autonomy in Strategic Digital Technologies through pre-commercial procurement (PCP action) (HORIZON-CL4-2022-RESILIENCE-02-PCP, 2022)
Start date: 2023-01-01
End date: 2026-08-31
Duration (months): 44.0
Total project cost (EUR): 8999735.0
EU funding (EUR): 8999735.0
Participants: 12
Project status: SIGNED

CircularPSP brings together 7 procurers from 7 countries, representing 45 million citizens, to invest €5.64 million in R&D to tackle the common challenge of accelerating digital transition towards a Circular Economy (CE). The Buyers Group represents highly attractive national markets (DE, FI, TR, SE, IE, PT, SI) supported by a Preferred Partner in UK, including capitals with global influence (Berlin, Helsinki, London, Istanbul). The consortium represents European CE-transition and PCP leaders in science and practice. Suppliers are expected to deliver a new green digital public service and data platform enabling entire municipal operations (city) and the local economy (market) to choose, open up, and consume existing and new data. The solution is to support business processes and workflows to plan, procure and implement innovative CE-solutions across Europe more quickly and at larger volume. The unmet procurement needs are: tools to improve organisational and operational performance; data analytics using taxonomies to exploit and exchange CE information and data; removal of language barrier to unlock EU-wide knowledge and learnings. To enable the transition suppliers will answer with ICT innovation in the cross-cutting combination and leveraging of existing and new strategic digital technologies: 1) scalable platforms for city and SMEs users, 2) CE data analytics using EU taxonomy, open linked data, injected by AI, and 3) natural language processing (NLP) to break language barriers across the EU and beyond. The envisaged solution is relevant for all European authorities including cities, ministries, agencies, and housing. Activity triggered by the solution will increase the volume of circular procurement and widen commercialisation opportunities for green digital companies and result in EU leadership in Circular Economy. With interoperability at the core and innovative tools for data sharing and open standards, the solution will provide a use case for the upcoming Common Industrial and Green Deal European Data.

Keywords: circular transition circular cities circular procurement ict public service platform digitisation ai nlp
Real-Time Urban Mobility Management via Intelligent UAV-based Sensing (URANUS)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Human Mobility, Environment, and Space
Panel description: Human geography, demography, health, susta inability science, territorial planning, spatial analysis
Countries involved: Cyprus
Call: ERC CONSOLIDATOR GRANTS (ERC-2022-COG, 2022)
Start date: 2023-07-01
End date: 2028-06-30
Duration (months): 60.0
Total project cost (EUR): 1999938.0
EU funding (EUR): 1999938.0
Participants: 1
Project status: SIGNED

Inefficient management of urban mobility leads to congestion with several socioeconomic and environmental adverse effects. Despite numerous research efforts and deployed technological solutions to address congestion, the problem still persists. One of the main reasons is attributed to the sparsity and low quality of traffic data. Unmanned Aerial Vehicles (UAVs) are an emerging, non-invasive, vision-based traffic sensing technology that offers economic viability and fast deployment. UAVs can swiftly and controllably move over disperse locations to capture road traffic data and simultaneously measure multiple traffic parameters. Despite these advantages, their applicability has so far been limited to occasional surveillance of road networks for live video monitoring or the extraction of historical traffic data. URANUS proposes real-time, dynamic, and continuous UAV-based sensing of vehicular and pedestrian traffic and the use of the collected information for UM management. The envisioned paradigm features: (a) intelligent spatiotemporal sampling from UAVs, (b) the generation of complete spatiotemporal measurement sets with quantified uncertainty, (c) the development of suitable methodologies to 'close the loop', by jointly controlling the urban mobility (UM) and UAV networks for enhanced UM performance, and (d) the strategic selection of measured parameters. In this context, URANUS will design a solid framework for real-time urban mobility management targeting both vehicular and pedestrian traffic. The developed framework will include UM monitoring, UM control, and UAV operational planning methodologies, exploiting the unique URANUS sensing characteristics. Success of this project will transform our understanding of joint optimization between sensing, monitoring, and control, not only in UM management but also in other UAV-centric fields such as air pollution monitoring.

Keywords: intelligent transportation systems,real time,uav based sensing,traffic monitoring,traffic control
Educational Inequalities and Generative AI: A Focus on Language Diversity (ChatEQUITY)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Soci al World and Its Interactions
Panel description: Sociology, social psychology, education  sciences , communication  studies
Countries involved: Belgium
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-09-01
End date: 2030-08-31
Duration (months): 60.0
Total project cost (EUR): 2195500.0
EU funding (EUR): 2195500.0
Participants: 1
Project status: SIGNED

ChatEQUITY investigates the impact of generative AI (GenAI) on educational inequalities amid growing societal linguistic diversity. The central hypothesis is that although multilingual GenAI can overcome linguistic barriers, mere access to it is insufficient because competent use is essential. Moreover, since GenAI language models are trained on and steered by human language—which reflects social class, ethnic, and gender differences—GenAI might reproduce biases and educational disparities. Research on this is lacking due to underlying limitations in the prevailing concepts, methods and data. ChatEQUITY addresses these with three objectives: 1. To introduce prompting (l)iteracy (PIL) as a novel concept for competent human-GenAI interactions and develop a pioneering assessment instrument (PIL-AI) for its measurement. 2. To identify shifts from traditional digital divides to GenAI divides—social disparities in GenAI access, use and skills —with innovative data from 3,000 students and 700 teachers across 60 high schools. 3. To evaluate the impact of GenAI use and PIL-education on educational inequalities by examining their effects on teaching and learning with three refined RCTs. ChatEQUITY enables researchers to move beyond merely observing the effects of GenAI, toward understanding why and how GenAI affects life outcomes. Because PIL-AI uniquely combines an authentic task-based approach with scalability, this tool marks a paradigm shift in the assessment of competencies that currently depends on self-reported measures. The open data on GenAI divides establish the groundwork for research into the interplay of sociological, pedagogical, linguistic, and technological factors. Finally, by refining traditional binary RCTs (moving beyond simple comparisons between tech and non-tech users), we recenter education in educational technology research. In essence, ChatEQUITY aligns with UNESCO’s call to promote equity through GenAI capacity-building in education and research.

Keywords: language diversity multilingualism educational inequality generative ai large language models
Deciphering autoreactive T cell immunity in human inflammatory peripheral neuropathies. (AUTO-T-NERVES)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Immunity, Infection and I mmunotherapy
Panel description: The immune system , related disorders  and their mechanisms , biology of infectious agents and infection, biological basis of prevention and treatment of infectious diseases , innovative imm unological tools and approaches , including  therapies
Countries involved: Italy
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-12-01
End date: 2030-11-30
Duration (months): 60.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 1
Project status: SIGNED

Guillain-Barré syndrome (GBS) is a rare heterogenous inflammatory peripheral neuropathy usually triggered by a preceding infection and causing a potentially life-threatening progressive muscle weakness. While the disease is generally considered to have an autoimmune basis, the underpinning immune-mediated mechanisms remain mostly elusive. This aspect poses a significant medical challenge in terms of accurate diagnosis, prognosis, and treatment. Building on our recent findings revealing that autoreactive T cell immunity play a key role in a subset of GBS patients, the project proposed herein aims at systematically elucidating its relative contribution to distinct GBS subtypes and disease stages. To this end, we will use cutting-edge technical approaches that enable the study of potentially rare autoreactive T cells in human biological samples (i.e. blood, cerebrospinal fluid and tissue biopsies) through three specific aims: Aim 1 is to perform in-depth immunophenotyping of blood-circulating immune cells for identification of potential variations in their frequency and distribution across GBS subtypes and stages; Aim 2 is to provide a systematic characterization of self-reactive T cells in patients’ biological samples by combining in vitro T cell screenings and ex vivo tetramers staining with high-throughput single cell analysis, such as single T cell clone generation, single cell RNA sequencing and TCR sequencing; Aim 3 is to dissect the cellular and molecular bases of cross-reactive T cell immunity in GBS by integrating in vitro sequential stimulation, single T cell clone generation and TCR sequencing with mass spectrometry-based immunopeptidomics or lipidomics. The outcomes of this project will significantly expand our understanding of the immunopathology of inflammatory peripheral neuropathies and advance our basic knowledge of human autoreactive T cell biology, with substantial implications for biomedical applications.

Keywords: autoreactive t cells,group 1 cd1 restricted unconventional t cells,guillain barr syndrome,inflammatory neuropathies,human immunology,cross reactivity
Price multipliers in the options market. (OPTDEM)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Economic Sciences
Countries involved: Portugal
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-09-01
End date: 2027-08-31
Duration (months): 24.0
Total project cost (EUR): 191343.12
EU funding (EUR): 191343.12
Participants: 1
Project status: SIGNED

A novel line of research suggests that financial assets react to demand similarly to other products; in contrast with the classical view of inelastic demand for financial products. This new paradigm implies that data on holdings is extremely useful for predicting price changes and creating counterfactual scenarios. Until now, empirical evidence focused on equities and, to a lesser extent, bonds supports the new paradigm. This project focuses on a different asset class, option derivatives. This financial product has grown exponentially in the last decade due to financial market improvements; therefore, demand has boomed, potentially elevating prices. The main question of this proposal is how much option prices rise due to an increase in demand. A high increase will make these instruments less attractive as hedging devices. Consequently, the investor base has shifted towards a more speculative base, including retailers whose participation has sky-rocketed in the last decade despite having realized enormous losses over the last few years. We need two main ingredients to assess the effect of demand on prices. First, we need investors' holdings. In contrast to equities and bonds, regulators in most countries do not require detailed derivative positions. This grant will use a novel dataset from Brazil, where the regulator forces funds to report all positions on any asset they hold (or short). Second, we need a method to disentangle which price movements are due to changes in demand. This grant will adapt the recently developed method of granular instrumental variables to options. I will develop this action at Nova SBE in Portugal under the supervision of Prof. M. Ferreira, where I will also receive training and career development to improve my skills. By joining Nova SBE, I will expand my network and strengthen complementary skills. In turn, I will bring my expertise in financial econometrics to significantly expand their research capacity.

Keywords: options,demand based asset pricing,derivatives