Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Biosensing by Sequence-based Activity Inference (BiosenSAI)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Biotechnology and Biosystems E ngineering
Panel description: Biotechnology using all organisms , biotechnology for environment  and food applications, applied plant and animal sciences , bioengineering and synthetic biology , biomass and biofuels , biohazards
Countries involved: Germany
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2024-02-01
End date: 2029-01-31
Duration (months): 60.0
Total project cost (EUR): 1499453.0
EU funding (EUR): 1499453.0
Participants: 1
Project status: CLOSED

The ability of cells to sense and respond to signals is an essential requirement of life. Genetically encoded biosensors meet this need by detecting, for example, chemicals and triggering gene expression in response. This concept is used across the life sciences to sense molecules in basic research, diagnostics and treatment. Crucially, biosensors can be used to isolate and engineer microbes that sustainably produce value-added chemicals and thus play a key role in the transition to a circular economy. However, native biosensors are mostly unfit for synthetic applications in terms of molecules and concentrations they respond to. Moreover, little is known about the relationship between biosensor sequence and resulting function, which prohibits rational biosensor engineering and enforces tedious, often unsuccessful trial-and-error approaches. I propose to build a pipeline for the rational engineering of biosensors with tailored sensory properties to overcome these limitations. Building upon an ultrahigh-throughput DNA-recording technique we have recently invented, we will generate hitherto inaccessible datasets linking over 10^8 transcriptional and translational biosensor sequences with their sensory properties and use these data to train deep learning models that infer biosensor function directly from sequence. This will enable straightforward biosensor design, which we will capitalize on to build a versatile biosensing platform to specifically detect and discriminate molecules from three metabolic compound classes with high potential for bio-based production. Finally, we will apply designed biosensors to engineer new enzymes for CO2-fixation and build dynamic metabolic controllers to obtain superior bacterial strains for the production of flavors and pharmaceuticals. Our novel, data-driven approach will break new grounds in biosensor engineering through synergies between synthetic biology and artificial intelligence paving the way to novel, sustainable bioprocesses.

Keywords: sequence function mapping,biosensor,transcription factor,riboswitch
Spatio-TEmporal Linked data tools for the AgRi-food data space (STELAR)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Digital
Destination: World-leading Data and Computing Technologies
Action type: Innovation actions
Partnership: AI-DATA-ROBOTICS (co-programmed)
Countries involved: Greece,Netherlands,Germany,Italy,Serbia
Call: Technologies for data management (AI, Data and Robotics Partnership) (IA) (HORIZON-CL4-2021-DATA-01, 2021)
Start date: 2022-09-01
End date: 2025-08-31
Duration (months): 36.0
Total project cost (EUR): 5678325.0
EU funding (EUR): 4845985.75
Participants: 9
Project status: SIGNED

STELAR will design, develop, evaluate, and showcase an innovative Knowledge Lake Management System (KLMS) to support and facilitate a holistic approach for FAIR (Findable, Accessible, Interoperable, Reusable) and AI-ready (high-quality, reliably labeled) data. The STELAR KLMS will allow to (semi-)automatically turn a raw data lake into a knowledge lake. This is achieved by (1) enhancing the data lake with a knowledge layer, and (2) developing and integrating a set of data management tools and workflows. The knowledge layer will comprise: (a) a data catalog offering automatically enhanced metadata for the raw data assets in the lake, and (b) a knowledge graph that semantically describes and interlinks these data assets using suitable domain ontologies and vocabularies. The provided tools and workflows will offer novel functionalities for: (a) data discovery and quality management; (b) data linking and alignment; and (c) data annotation and synthetic data generation. The KLMS will combine both human-in-the-loop and automatic approaches, to leverage background knowledge of domain experts while minimizing their involvement. To reduce manual effort and time, it will increase the automation of finding and selecting relevant data sources, configuring, and tuning the involved data management tools, and designing, executing, and monitoring end-to-end data processing workflows adapted to different user needs. The KLMS will include specialized tools and functions for geospatial, temporal, and textual data. An organization, ranging from a data-intensive SME to the operator of a data marketplace, will be able to use the STELAR KLMS to increase the readiness of its data assets for use in AI applications and for being shared and exchanged within a common data space. The STELAR KLMS will be pilot tested in diverse, real-world use cases in the agrifood data space, one of the nine data spaces of strategic societal and economic importance identified in the European Strategy for Data.

Keywords: data discovery,data linking,data annotation,agrifood data space
Wage Negotiations and Gender Pay Gaps: Exploring the Role of Fairness Attitudes in Europe (FAIRGAP)

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: Germany
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): 1999955.0
EU funding (EUR): 1999955.0
Participants: 1
Project status: SIGNED

In the EU, addressing the gender pay gap, defined as the difference in earnings between men and women, is a significant policy challenge. Despite concerted efforts, this disparity persists, exhibiting noticeable differences across member states. Recent changes in the European labor market, such as the reduced role of unions and the shift towards individual pay negotiations, may amplify these disparities. Individual pay negotiations increase the responsibility of employees in determining their pay. Men typically achieve more favorable outcomes than women in these individual pay negotiations. Thus, the increasing prevalence of individual pay negotiations in Europe may lead to the widening of the gender pay gap. A vital aspect of this research is the focus on fairness norms in pay negotiations and their impact on the gender pay gap. Prior research reveals that perceptions of pay fairness are often subconsciously skewed against women. This project explores under what conditions pay fairness attitudes develop a gender bias and how they subsequently influence the outcomes of pay negotiations. To investigate this, I will conduct unique surveys across selected European countries, examining the origins of gender-biased fairness attitudes and their effect on negotiation behaviors and the gender pay gap. These surveys will incorporate experimental elements to assess causal relationships. By integrating these empirical studies within a unified theoretical framework, the project seeks to offer a comprehensive understanding of gender biases in pay negotiations and their broader implications for the labor market. In sum, this project tackles a vital gap in our knowledge regarding the gender pay gap, focusing on the influence of fairness norms in wage negotiations. It represents a critical advancement in labor market research and holds the potential to guide future policies aimed at reducing gender inequalities in the workplace.

Keywords: pay fairness,justice,pay negotiations,gender bias,europe
Making Sense of the Unexpected in the Gravitational-Wave Sky (GWSky)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Synergy grants
Action type: ERC actions
Countries involved: Germany,United States,Italy,Denmark
Call: ERC SYNERGY GRANTS (ERC-2024-SyG, 2024)
Start date: 2025-04-01
End date: 2031-03-31
Duration (months): 72.0
Total project cost (EUR): 11982258.0
EU funding (EUR): 11982258.0
Participants: 4
Project status: SIGNED

General Relativity (GR) is more than a century old, but is still our best macroscopic description of gravity. Key GR predictions are black holes (BHs) and gravitational waves (GWs), whose spectacular confirmation led to two recent physics Nobel Prizes. The future of GW astronomy, however, is even brighter, since detectors will observe BHs at cosmic dawn and probe their enigmatic event horizon, where GR clashes with quantum mechanics in the information loss paradox. These experiments will measure signals hundreds of times smaller than today, necessarily discovering anomalies and deviations from current predictions, e.g., due to the astrophysical environment. On the fundamental side, precision GW astronomy will open countless possibilities for understanding the standard model of particle physics (and its extensions), gravity and cosmology. By itself, however, precision is not knowledge. To harness the power of these measurements, a groundbreaking framework is urgently needed to solve the very nonlinear equations of GR and develop waveform models to unprecedented accuracy, and to convert these results into concrete interpretation tools. GWSky will leverage the world-leading expertise of its PIs in astrophysics, GW-source modeling, particle physics and GR, and recent paradigm shifts to build an overarching framework answering a fundamental question: When, inevitably, an anomaly in a GW signal is identified, what is it? A gravitational effect not predicted by GR? The influence of nearby matter? Or merely an imprecise calculation of the expected signal? Even tiny deviations from GR would shake physics to its core, but to claim a deviation from it, one needs to filter out first the contributions from the astrophysical environment, instrumental artifacts and systematic modeling uncertainties. GWSky will provide tools to disentangle these contributions, enabling precision GW astronomy with upcoming observational runs, and new facilities on the ground and in space.

Keywords: the two body problem in general relativity
European Advanced Materials Academy: Securing Europe's materials leadership through skilled and future-ready talents (AdMatAcademy)

Framework: Horizon Europe — Innovative Europe
Programme: The European Institute of Innovation and Technology (EIT)
Theme: other EIT
Destination: other EIT
Action type: Knowledge and Innovation Communities
Countries involved: Germany
Call: European Advanced Materials Academy (HORIZON-EIT-2024-ERMA-EAMA-IBA, 2024)
Start date: 2025-01-15
End date: 2029-01-14
Duration (months): 48.0
Total project cost (EUR): 14000000.0
EU funding (EUR): 9800000.0
Participants: 2
Project status: SIGNED

The European Advanced Materials Academy is a transformative initiative to position the European Union at the forefront of advanced materials innovation, enabling the twin transition towards sustainability and digitalisation while ensuring global industrial leadership. Despite the critical role advanced materials play, the field is constrained by a lack of skilled talent. The Academy aims to address this challenge by equipping Europe with the current and future skills necessary to lead in this arena. The Academy's goal is to become a globally recognised, game-changing materials learning and talent hub, powered by a revolutionary, one-stop-shop platform that unites 4 key stakeholders: workers, learners, employers, and educators. It integrates the latest workforce agility and skills intelligence technologies to provide personalised learning pathways, real-time skills data, and innovative solutions. Led by EIT RawMaterials and EIT Manufacturing, and in collaboration with the most important actors in advanced materials, the Academy is set to disrupt the traditional talent development and recruitment landscape. Its approach begins with the creation of a high-quality solutions portfolio, institutional accreditation, and credentialing system. Through partnerships with education and training providers across the EU, the Academy ensures wide access to its offerings. A massive marketing and communications campaign amplifies its reach, while stakeholder collaborations guarantee its long-term impact. Financial sustainability is built into the model, ensuring the Academy continues well beyond the project’s initial phase. With a focus on inclusivity and innovation, the Academy envisions a thriving community of skilled and future-ready talents driving Europe’s advanced materials field. The initiative not only fills a critical skills gap but also lays the foundation to revolutionise global standards, aligning with the EU’s broader sustainability and industrial leadership goals.

Keywords: advanced materials,workforce,skills,skills development,learning and talent platform
Fostering Oncology Research by Charities in Europe (FORCE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Mission
Theme: Cancer
Destination: Cancer
Action type: Coordination and support actions
Countries involved: France,Spain,Belgium,Netherlands,Sweden,Italy,Ireland,Greece,Hungary,Poland,Latvia
Call: Support a pragmatic clinical trial programme by cancer charities (HORIZON-MISS-2024-CANCER-01, 2024)
Start date: 2025-06-01
End date: 2029-05-31
Duration (months): 48.0
Total project cost (EUR): 3400125.0
EU funding (EUR): 3350104.75
Participants: 14
Project status: SIGNED

The 'Fostering Oncology Research by Charities in Europe' consortium (FORCE) is a network of 15 European charities across 12 European countries joining forces to support pragmatic clinical trials tackling high and unmet medical needs in oncology in Europe. The main objective of the FORCE CSA is to provide the Mission Board with an ambitious, yet feasible, programme by & for cancer charities, to optimize their contribution to the Europe’s Beating Cancer Plan. The Pragmatic Clinical Trial Programme will be elaborated in a bottom-up coordinated approach, involving all relevant stakeholders (researchers and professionals from different disciplines, patients, citizens, policy makers and regulatory authorities) across Member States and Associated Countries. During the CSA, the FORCE consortium will propose foundational pillars for EU strategic support to a European cancer charities network dedicated to organising, implementing and monitoring sustainable and ambitious support for cancer pragmatic clinical trials. The overall objectives of this initiative are to: 1. Define and deliver a Pragmatic Clinical Trial Programme by cancer charities; 2. Implement two transnational calls to test and improve our proposed programme (feasibility step); 3. Deliver to the EC a blueprint on pragmatic oncology clinical trials by charities to facilitate decision-making and provide guidelines for the future work programme. Through the successful achievement of these objectives, the FORCE network will both strengthen cooperation among European cancer charities and mobilise the European research community through crucial scientific questions to improve health outcomes for cancer patients through patient-focused research. This action is part of the Cancer Mission cluster of projects on "Diagnostics and treatment".

Keywords: charities pragmatic clinical trial programmes transnational calls practice changing research hard to treat cancers rare cancers
Phase Field Digital Twin Framework for Composite Structural Safety Evaluation accounting for Uncertainty (PFDT-CSSE)

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: Information Science and Engineering
Countries involved: United Kingdom
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): 276187.92
EU funding (EUR): 276187.92
Participants: 1
Project status: SIGNED

This project is devoted to developing a rapid adaptive Digital Twin-based phase field fracture modelling technique, which will provide accurate prediction of damage initiation and propagation for advanced composite materials and structures servicing in extreme, multi-physics environments. This proposed rapid adaptive digital twin-based fracture computational framework will establish a direct connection and mapping between virtual simulations and real-world composite structural behaviours under multiphysics environments. A virtual modelling aided stochastic interval method will be applied for the quantification of system and multiphysical uncertainties. A computationally efficient fracture simulation technique, based on the Phase Field Cohesive Zone Model (PFCZM) and Broyden–Fletcher–Goldfarb–Shanno (BFGS) monolithic algorithm, will be developed to accurately predict the complex crack behaviours (nucleation, propagation, merging and branching, etc.) for advanced composite materials and structures (3D printed, lattice, FGM, FRP etc.). This action will, for the first time, overcome a series of technique challenges in the modelling and analysis of non-deterministic multi-physics fracture problems encountered in composite structures include: the damage diagnosis by fussing multi-physical sources of data; the high-fidelity computational complexity of composite crack simulation methods; identification, quantification and validation of uncertainty factors in damaged system under thermo-mechanical, chemo-mechanical, and electromechanical coupling conditions. Finally, the accurate fracture prediction methods developed in this project will enable rapid safety and reliability evaluation for advanced composite structures. Through this fellowship, the applicant, in conjunction with the team at Cardiff University (CU) will deliver internationally recognized research outcomes and techniques for advanced composite structures safety analysis and evaluation.

Keywords: digital twin,phase field,composite material,non deterministic fracture,reliability assessment,safety evaluation
Cryosphere-hydrosphere-lithosphere interactions under changing climate in Arctic (CryArctic)

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: Sweden
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-01-01
End date: 2026-12-31
Duration (months): 24.0
Total project cost (EUR): 206887.68
EU funding (EUR): 206887.68
Participants: 1
Project status: SIGNED

The rapid climate warming in Arctic leads to formation of extensive offshore groundwater reserves through submarine permafrost and subglacial melt water drainage. There is increasing evidence that cryosphere driven submarine groundwater discharge (SGD) is prevalent in continental shelf and slope regions of Arctic Ocean, but controls of elemental fluxes through SGD remains uncertain. The CryArctic project closely investigates how cryosphere driven groundwater flow, occuring in timescales from days to millennium, interacts with the permeable sediments (silicates and carbonates) in coastal aquifers and seafloor. The solute delivery and associated source/sinks of submarine groundwater flow remains unknown and are gaps in our current understanding of Earth’s cryosphere and biogeochemical cycling. The project aims to provide elemental and isotopic composition of submarine groundwater endmember through extensive analysis of marine porewater from six locations pan-Arctic where SGD is documented. Through state-of-the-art silicon (Si) and strontium (Sr) isotopic measurements of marine porewater, terrestrial endmembers and other leached fractions we will be able to decipher dominant biogeochemical process occuring within the subterranean mixing zones. We supplement the high resolution isotopic measurements with scanning electron microscopy and X-ray diffraction to identify major authigenic and detrital phases in sediments. The project will be the first to couple Si and Sr isotopes in marine porewater and results will have implications for solute delivery through SGD and silicate alteration pathways in marine sediments. Through MSCA fellowship, candidate aim to acquire skills for long term research planning, advanced instrumental training, form international collaborative networks, and most importantly gather the attention of scientific community as well as public towards the magnitude and relevance of Arctic SGD.

Keywords: submarine groundwater discharge,silicate weathering,carbonate weathering,silicon isotopes,groundwater resources
Using deep neural networks to understand functional specialization in the human visual cortex (DEEPFUNC)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Human Mind and Its Compl exity
Panel description: Cognitive science, psychology, linguistics
Countries involved: Germany
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): 1494750.0
EU funding (EUR): 1494750.0
Participants: 1
Project status: SIGNED

Over the last few decades, neuroscientists have identified multiple brain regions that perform distinct, often highly specialized functions such as processing faces, understanding language, and even thinking about what other people are thinking. Despite our increased understanding of the computations performed in these regions, the precise causes and origins of functional specialization in the brain are still a mystery and not accessible to direct experimental approaches. Here, we propose to combine cutting-edge computational modelling, large-scale sampling of naturalistic behaviour and human neuroimaging to overcome these limitations. Focusing on visual perception, we will exploit the latest advances in artificial neural networks to probe three critical aspects of functional specialization in the ventral visual pathway: First, by training networks on natural and artificial visual categories and identifying which features result in functional specialization, we will characterize what it is about a visual category that leads to functional specialization. Second, we will leverage large-scale egocentric datasets of infant and adult visual input to test how visual experience and natural input statistics shape functional specialization during development. Third, we will ask why certain neural features become specialized for high-level visual categories in the human visual cortex in the first place. Critically, for each of these aspects, we will close the loop and directly test and validate its predictions in the human brain. Our project will shed light on functional specialization from a new angle – by relating functional specialization to the computational constraints of performing tasks in the real world. Using this novel approach, our project tackles some of the most fundamental questions about the functional organization of the human mind and brain – the what, how and why of functional specialization.

Keywords: functional specialization,deep neural networks,fmri,eeg,ventral visual pathway,natural vision,face perception,task optimization