Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Spatiotemporal regulation of centriolar satellite homeostasis (SatelliteHomeostasis)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Cell Biology, Development, Stem Cells and R egeneration
Panel description: For all organisms : Structure and function of the cell, cell -cell communication, embryogenesis, tissue differentiation, organogenesis, growth, development, evolution of development, organoids, stem cells, regeneration, therapeutic approaches
Countries involved: Türkiye
Call: ERC STARTING GRANTS (ERC-2022-STG, 2022)
Start date: 2023-11-01
End date: 2028-10-31
Duration (months): 60.0
Total project cost (EUR): 1588710.0
EU funding (EUR): 1588710.0
Participants: 1
Project status: SIGNED

Membrane-less compartmentalization has emerged as a powerful, yet mysterious, process for the spatiotemporal control of fundamental cellular processes. How the identity of a membrane-less organelle is established, maintained, and dynamically altered remains unclear. In this project, I will investigate the fascinating biology of the centriolar satellites (hereafter CS), a vertebrate-specific membrane-less organelle. CS was first discovered as granules that cluster and move around centrosomes – major microtubule-organizing centers of animal cells. Recently, my lab and others have placed CS in a new pathway for targeting proteins to centrosomes and cilia, and identified an important role for CS in cell division, cellular signalling and neurogenesis. While CS functions shone light in these organelles, little is known about their own biochemistry and how that affects their function. Recent studies, including my own, revealed unique and intriguing CS properties that likely underlie the rules underpinning their regulation and function. The properties of CS granules are regulated in space, time and tissue, as we observe differential size and composition within the cell and in different cell types. Building on these discoveries, I hypothesise that CS perform its different functions by acting as adaptive organelles that remodel its granule features in response to intrinsic and extrinsic cues. With this project I propose to investigate the molecular basis of (1) CS scaffold assembly and disassembly, (2) CS granule size, composition, architecture and dynamics; and (3) CS heterogeneity within a cell and in different cell types. This project will combine in vitro reconstitution, imaging-based assays, a new SatelliteGFP mouse and our expertise in proximity proteomics and biochemical purifications. Our results will have broad implications in unveiling how cells organize its cytoplasm in time and space appropriate to its differentiation status, environment and organismal health.

Keywords: centriolar satellites,cilia,primary cilium,motile cilia,centrosome,microtubule organizing center,microtubules,mitosis,membrane less organelles
Training Alliance for Computational Systems chemistry (TACsy)

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: Chemistry
Countries involved: Denmark,United States,United Kingdom,Austria,Germany,France
Call: MSCA Doctoral Networks 2021 (HORIZON-MSCA-2021-DN-01, 2021)
Start date: 2023-03-01
End date: 2027-02-28
Duration (months): 48.0
Total project cost (EUR): 3872336.4
EU funding (EUR): 3872336.4
Participants: 11
Project status: SIGNED

Many important questions and grand challenges in research, industry, and society involve large and complex networks of chemical reactions. Some examples are: studying metabolic networks in humans; planning and optimizing chemical synthesis in industry and research labs; modeling the fragmentation process in mass spectrometry; developing personalized medicine; probing hypotheses of the origins of life; monitoring environmental pollution in air, water, and soil. In project TACsy, we will develop ground-breaking new computational methods for analyzing such networks of chemical reactions and we will train a new generation of excellent and innovative early stage researchers (ESRs) capable of evolving and applying these methods in research and industry. Combined, these efforts carry very strong potential for impact on the grand challenges mentioned above, on the EU commission priority on jobs, growth, investment, and competitiveness, and on the well-being of EU citizens. The research methodology of TACsy arises from the novel application of formalisms, algorithms, and computational methods from computer science to questions in systems chemistry. The first steps demonstrating the strong capabilities of this approach have recently been made. In TACsy, the ESRs will vastly expand these methods and their formal foundations, they will create efficient algorithms and implementations of them, and they will use these implementations for research in complex chemical systems in three flagship application areas. TACsy is a consortium of world-class, experienced scientists which will ensure excellent research training conditions for the ESRs in this highly interdisciplinary field. Through a carefully designed training programme and secondments at leading industry partners, the ESR will acquire a broad career perspective and a strong set of transferable skills. Their unique blend of competences from computer science and chemistry will further increase their high employment.

Keywords: systems chemistry,efficient algorithms,large chemical reaction networks
Quantum Long-Range Networks (QLR-Net)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Fundamental Constituents of Matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Italy
Call: ERC STARTING GRANTS (ERC-2022-STG, 2022)
Start date: 2024-04-01
End date: 2029-03-31
Duration (months): 60.0
Total project cost (EUR): 1497801.0
EU funding (EUR): 1497801.0
Participants: 2
Project status: SIGNED

Long-range interactions enable a wide range of novel scaling phenomena in the out-of-equilibrium behaviour of quantum systems. These dynamical phases are particularly relevant to quantum computation as they feature enhanced coherent properties and fast spreading of quantum correlations. Currently, long-range interacting systems evade description in terms of the conventional many-body theory toolbox due to their high-connectivity and to the appearance of metastable states, which pose a formidable challenge to state- of-the-art numerical simulations. QLR-Net hinges on the construction of a unified tool, exemplified in terms of a prototypical many-body theory model, which reproduces the spectral properties of long-range interactions in a modular structure amenable to extensive numerical investigations. Then, the project will focus on the spreading of quantum correlations and entanglement, anomalous dynamics and ergodicity breaking, universal quasistatic dynamics, dynamical phase transitions, pre-thermal phases and universal defect formation. The QLR-Net approach is organized in such a way to provide both basic intuition and formal understanding, while making quantitative predictions for scaling phenomena that can be realised in experiments. The study of quantum long-range networks will provide at least two solid paths to uncover new physics: 1) First, by reproducing the low-energy physics of long-range interactions in a system with “reduced" connectivity it will give access to novel phenomena, which shall also appear in fully-connected long-range interacting systems. 2) Secondly, it will provide quantum many-body theory with a novel toolbox to understand critical phenomena in non-homogeneous systems and their role as a source of fresh and vital problems, which could be realised in atomic molecular and optical experiments. QLR-Net will open a new era of many-body theory, where novel dynamical phases are realised by tuning the low-energy property of interacting systems.

Keywords: long range interactions,out of equilibrium quantum matter,critical phenomena,universal scaling
Researchers in the Knowledge triangle (K-TRIO)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: European Researchers' Night
Action type: Coordination and support actions
Countries involved: Bulgaria
Call: European Researchers' Night 2022-2023 (HORIZON-MSCA-2022-CITIZENS-01, 2022)
Start date: 2022-03-15
End date: 2024-01-14
Duration (months): 22.0
Total project cost (EUR): 297142.0
EU funding (EUR): 297142.0
Participants: 11
Project status: CLOSED

In 2006, Sofia University (K-TRIO coordinator) as EURAXESS bridgehead organisation involved the newly established Bulgarian network in the first Researchers Night. Since then, it organised 14 European Researchers Nights, and attracted several new partners from education, research and industry. The overall K-TRIO objective coincides with the goal of the MSCA & Citizens action: "to bring research and researchers closer to the public at large, to increase the awareness of research and innovation activities and to boost public recognition of science and research education", and “to show the role of researchers for science and economy, as well as the impact of researchers’ work on citizens’ daily lives”. The strategic long-term objectives are: fostering the interest of young talents to STEAM and research career, nurturing a new culture of creativity, scientific curiosity, innovative spirit and responsibility to environmental preservation, as well as enhancing the public readiness to engage in Citizens Science, Open Science and Open Innovation activities. The Consortium will pay due attention in all pre-events and 2022-23 ERNs on the importance of the ERA and EEA, and their synergy, for the European recovery, dual transformation and knowledge-based growth. The project will create greater understanding on EU policy, and how R&I contribute for well-being of people and sustainable development, and highlight the common European efforts for bridging global challenges, building Green Economy and Digital Single market, Smart Cities and Smart Factories, and take full advantage of Clean Technologies, Internet of Things (IoT), Artificial Intelligence, BIG Data and Cloud computing. The R&I role in resolving present COVID crises will be also highlighted. The already established networking with teachers, schools and STEM centres will become well-structured, and will integrate many researchers in mentoring of students or events in secondary schools and partners universities.

Keywords: new research generations,young talents,steam,researchers night
DeepLearning 2.0: Meta-Learning Qualitatively New Components (DeepLearning 2.0)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2021-COG, 2021)
Start date: 2022-05-01
End date: 2027-04-30
Duration (months): 60.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 1
Project status: SIGNED

Deep learning has revolutionized many fields, such as computer vision, speech recognition, natural language processing, and reinforcement learning. This success is based on replacing domain-specific hand-crafted features with features that are learned for the particular task at hand. The logical step to take deep learning to the next level is to also (meta-)learn other hand-crafted elements of the deep learning pipeline. We therefore propose to develop meta-level learning methods for the creation of novel customized deep learning pipelines, by means of: 1. Hierarchical neural architecture searchfor learning qualitatively new architectures and architectural building blocks from scratch; 2. Learning of optimizers and hyperparameter adaptation policies that adapt totheir context in order to converge faster and more robustly; 3. Learning the data to train on, to remove the need for large sets of labelled data; and 4. Bootstrapping from prior design efforts to increase efficiency and make an integrative design of architectures, optimizers, hyperparameter adaptation policies, and pretraining tasks feasible in practice. These advances will allow the next generation of deep learning pipelines to achieve higher accuracy, lower training time, and improved ease-of-use (democratization of deeplearning). They will also allow a customization to particular design contexts, including additional objectives next to accuracy (such as robustness, memory requirements, energy consumption, latency, interpretability, training cost, uncertainty estimation, and algorithmic fairness) in order to facilitate trustworthy AI. In order to demonstrate the effectiveness of these methods, we plan to develop: 5. New state-of-the-art customized deep learning pipelines for various applications, including EEG decoding, RNA folding, and improving the reinforcement learning pipeline and deep learning on tabular data.

Keywords: meta learning,learning to learn,automl,neural architecture search,hyperparameter optimization,data augmentation,reinforcement learning,eeg decoding,rna folding
Navigating volatility in different welfare state contexts (VOLARE)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting 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 STARTING GRANTS (ERC-2025-STG, 2025)
Start date: 2026-09-01
End date: 2031-08-31
Duration (months): 60.0
Total project cost (EUR): 1841705.0
EU funding (EUR): 1841705.0
Participants: 1
Project status: SIGNED

Income targeting has permeated social policy design in European welfare states, in order to boost their efficiency and effectiveness. Yet real-life examples of integrated income-targeted schemes highlight the shortcomings of an overly technocratic view. Social policy research needs to analyse how policy design interacts with the month-to-month income variability experienced by households, and the strategies they develop to cope with and navigate this volatility. VOLARE disentangles the relationship between fluctuating incomes, household navigating strategies and social policy design in different institutional contexts. VOLARE’s theoretical framework argues that a) households employ both formal and constrained strategies in the face of volatile incomes, that can be focused on short-term juggling of incomes, or oriented towards longer-term objectives; b) the welfare state context and households’ preferences for stability influence the adopted strategies, but c) with their strategies households also actively navigate the eligibility and entitlement criteria determining the accessibility, timeliness and effectiveness of social policy responses. VOLARE assesses the implications of this interaction for effective social policy design. The framework is scrutinized empirically within an innovative mixed-methods design that links consecutive quantitative monthly incomes collected among over 240 low to middle-income families in four European countries, with in-depth interviews on the strategies selected households develop to navigate volatile incomes. These findings are confronted with nationally representative month-to-month volatility estimates and welfare state responses. A survey experiment adds further substance as to how households value stability over income, given their access to formal or constrained navigating strategies. In doing so, VOLARE forces a major breakthrough in the research on income volatility, social policy effectiveness and household strategies.

Keywords: income volatility,social policy design,timeliness,targeting,navigating strategies
POLARIN: POLAR RESEARCH INFRASTRUCTURE NETWORK (POLARIN)

Framework: Horizon Europe — Excellent Science
Programme: Research infrastructures
Theme: Research infrastructures
Destination: Services and infrastructures
Action type: Research and Innovation actions
Countries involved: Germany,Finland,Sweden,Italy,Denmark,France,Netherlands,Norway,Spain,Ukraine,Portugal,Iceland,Greenland,Canada,Austria,Poland,United States,Ireland,United Kingdom,Bulgaria,Chile,Faroe Islands,Türkiye,Czechia,Japan
Call: Research infrastructure services to enable R&I addressing main challenges and EU priorities (HORIZON-INFRA-2023-SERV-01, 2023)
Start date: 2024-03-01
End date: 2029-02-28
Duration (months): 60.0
Total project cost (EUR): 14588116.68
EU funding (EUR): 14588114.0
Participants: 55
Project status: SIGNED

The polar regions play a key role in the Earth’s system. They are essential for our climate and are sentinels of climate change, human expansion, and the hunt of new resources. The polar regions are losing ice, and their oceans and land are changing rapidly. The consequences of this polar transition extend to the whole planet and are affecting people in multiple ways. Evidence-based policy recommendations are needed, but the polar regions are difficult to reach, and research infrastructures able to operate in these regions are scarce. To understand and predict key processes in the polar regions and provide evidence-based information, the polar research community needs access to world-class research infrastructure operating in these regions. POLARIN is an international network of polar research infrastructures and their services, aiming at addressing the scientific challenges of the polar regions. The network includes a wide array of complementary and interdisciplinary top level research infrastructures: Arctic and Antarctic research stations, research vessels and icebreakers operating at both poles, observatories, data infrastructures and ice and sediment core repositories. POLARIN will provide integrated, challenge-driven, and combined access to these infrastructures to facilitate interdisciplinary research on complex processes. POLARIN will: 1. Provide challenge-driven transnational access to a large portfolio of research infrastructures. 2. Improve the access to data by improving data availability and interoperability between data infrastructures. 3. Provide virtual access to data and data services. 4. Provide data products for the scientific community and decision makers. 5. Train the young generation of polar researchers in optimally exploiting the infrastructures for their research. 6. Duly advertise the services offered by POLARIN and engage the infrastructure users to share their research outcomes with society.

Keywords: polar research,arctic,antarctic,challenges,research infrastructures,services,infrastructure users,transnational access,virtual access,training,
Understanding The Fluid Mechanics of Algal Bloom Across Scales (FluMAB)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting 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: Netherlands
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2024-01-01
End date: 2028-12-31
Duration (months): 60.0
Total project cost (EUR): 1499838.0
EU funding (EUR): 1499838.0
Participants: 1
Project status: SIGNED

One of the most life-threatening consequences of global warming is the perturbation of natural ecosystems. Among the detrimental impacts, the increased frequency and intensity of Cyanobacterial blooms (overgrowth of microscopic bacteria in aquatic systems) seriously threaten drinking water and devastate ecosystems and the economy. The challenge now is to accurately predict the formation of Cyanobacterial bloom and find feasible mitigation strategies. This poses a new paradigm in complex fluids and flows where rheology, fluid mechanics, and biophysics are intertwined across scales: (1) rheological properties on the microorganism level (few microns), (2) mesoscopic phenomena of formation and fragmentation of Cyanobacterial colonies (hundreds of microns), and (3) macroscopic dispersion of colonies under laminar and turbulent flows in the aquatic system (meters). Hence, fundamental knowledge of rheology and fluid mechanics of Cyanobacterial bloom formation is urgently needed. I will tackle this multiscale problem with a set of highly controlled laboratory experiments and numerical simulations. The novel experimental setups combine rheological methods with advanced mechanical manipulation of cells, tomography, particle tracking, flow visualization, and microscopy. The combination of experiments, statistical modeling, and simulations will result in many first-ever measurements and analyses, unravelling the rheological and mechanical properties of the cells/colonies, and revealing details of aggregation and fragmentation of Cyanobacterial colonies under various hydrodynamic and environmental conditions. This project lays out an ambitious effort to overcome current limitations and uncover the complex multiscale interactions between rheology, fluid mechanics, cell biophysics, and colony formation and fragmentation. My findings will open new avenues in creating prediction tools and effective solutions to combat Cyanobacterial bloom.

Keywords: viscoplastic fluids