Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
ZPARQ Z10: Challenging the Limits of Marine Propulsion (ZPARQ-Z10)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Open to supporting projects in all areas of science, technology,...
Action type: EIC actions
Countries involved: Sweden
Call: EIC Accelerator Open 2025 (HORIZON-EIC-2025-ACCELERATOR-02, 2025)
Start date: 2025-09-01
End date: 2027-08-31
Duration (months): 24.0
Total project cost (EUR): 3570475.0
EU funding (EUR): 2499332.5
Participants: 1
Project status: SIGNED

Sea leisure and commercial vessels, as well as other watercraft, are mainly based on combustion engines which release large amounts of CO2 and other emissions (NOx, SOx, CO…), as well as, pollute water due to fuel and oil leakages. While regulations are promoting new electric systems, current designs are still far from maximum efficiency as these are based on internal combustion engine designs. At Zparq, we have developed an innovative cooling system that allows us to reduce the size of our POD motor, which is now 10 times smaller in weight and volume than any other existing POD motor in the market. This enables a breakthrough outrunner direct drive technology that brings lower TCO (-40%), lower energy cost and higher efficiencies (+15%), lower drag and longer range for a given energy consumption. On top of that, thanks to our novel engineering design, the footprint associated to the manufacturing of our system is reduced 50% compared to existing competitors. Plus, our system is highly modular and flexible and can be installed in any configuration like outboard, azimut thruster, saildrive, sterndrive or hydrofoil and can be scaled to any power range. Now we aim at optimising our system, scale it to higher power ranges, finalise the control platform including energy management and smart sailing features and validate our solution through several pilots in different type of end users.

Keywords: electric outboard,cooling systems,pod motor,maritime electromobility,leisure and commercial watercraft,aquatic electric propulsion,eco designed propulsion system
3D Nanoscope: a highly accessible, high-performance device for live cell nanoscopy (3DNanoScope4All)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Attracting and mobilising the best talents
Destination: Attracting and mobilising the best talents
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Portugal,United Kingdom,Spain
Call: ERA Fellowships (HORIZON-WIDERA-2023-TALENTS-02, 2023)
Start date: 2024-05-15
End date: 2026-05-14
Duration (months): 24.0
Total project cost (EUR): 156778.56
EU funding (EUR): 156778.56
Participants: 4
Project status: SIGNED

Contemporary optical microscopy techniques are capable of imaging sub-wavelength (<400nm) structures. However, challenges such as phototoxicity, slow acquisition speeds, and difficulties in extending to 3D imaging have hindered their widespread adoption in live-cell studies. Light field microscopy (LFM) allows 3D imaging of biological samples with a single snapshot, reducing phototoxicity and allowing fast imaging of whole live cells. Recent breakthroughs have demonstrated single-molecule LFM with sub-100nm resolution, offering a straightforward optical design that holds immense promise for integrating complementary methods to study real-time dynamics in live cells without causing damage. 3DNanoScope4All will develop and formalise a highly accessible, high-performance device for live cell nanoscopy. For that, three novel, yet robust, techniques will be merged in a single device: (i) LFM as the core technique, (ii) 3D-SRRF, facilitating high-resolution, rapid measurements and (iii) single-molecule orientation microscopy, providing spectroscopic insights into 3D molecular order. The combination of these cutting-edge technologies will enable both structural and dynamic measurements of live cells in a powerful yet affordable device. After validation, this nanoscope will be used to reveal previously poorly understood processes involved in the dynamics between viral particles (120nm) and cell membrane interactions during human immunodeficiency virus (HIV) infection. These advancements will not only broaden the current understanding of HIV infection but also pave the way for future research based on super-resolution microscopy techniques applied to other host-pathogen interactions.

Keywords: super resolution microscopy,single molecule polarization,radial fluctuations,light field microscopy,single molecule,hiv 1,plasma membrane,infection cycle,live cell
Data Driven Game Theoretic Control for Constrained Systems (ARGON)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Countries involved: Netherlands
Call: ERC CONSOLIDATOR GRANTS (ERC-2025-COG, 2025)
Start date: 2026-06-01
End date: 2031-05-31
Duration (months): 60.0
Total project cost (EUR): 1999388.75
EU funding (EUR): 1999388.0
Participants: 1
Project status: SIGNED

The European society relies heavily on large-scale infrastructures, e.g. power and gas grids, transportation networks, with interconnected and self-interested sub-systems, e.g. networked control units, semi-autonomous robots, intelligent machines and humans. Due to high complexity, variability and uncertainty of their real-life operations, accurate dynamic, behavioral and interference models are hardly available. Nevertheless, the deployed control systems are either simplistic regulators or advanced controllers based on unreliable models. Model-based game theory and distributed optimization have attracted extraordinary research attention but in real-life practice are ineffective for control design due to the unavailability of reliable models and the limited information exchange between sub-systems. Data-driven optimal control has emerged as a practical control approach to mitigate model awareness, but only for cooperative systems. A paradigm shift is thus necessary to ensure safe, fair and efficient operation in systems with self-interested sub-systems. With this aim, ARGON will initiate the whole new area of data-driven dynamic game theory for constrained systems and in this scientific context it will pursue the twofold objective to: (i) conceive a general data-driven game-theoretic control framework; (ii) provide fast and scalable computational methods for solving data-driven decision and control problems. Towards these objectives, ARGON will develop novel methodologies based on distributionally robust operator theory and feedback control for equilibrium seeking, and integrate new ideas across monotone game theory, Lyapunov stability theory for constrained systems, data-driven control of switched systems. The expected outcomes are a mathematical theory and computational algorithms to support control synthesis in systems with self-interested, constrained sub-systems, robustly to model uncertainty, with high impact on fundamental sciences and system engineering.

Keywords: generalized nash equilibrium seeking,control lyapunov functions,constrained switched systems
Exploring the role of copper as as a driver of Vibrio aestuarianus emergence and niche specialisation as an oyster pathogen (VibOysCopper)

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: France
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2024-06-01
End date: 2026-05-31
Duration (months): 24.0
Total project cost (EUR): 211754.88
EU funding (EUR): 211754.88
Participants: 1
Project status: SIGNED

Oceans health is intimately linked to animal and human health in a One Health framework. Marine zoonotic diseases threaten animal and human health and well-being, ecosystem integrity and economic development of marine coastal systems. Coastal waters, where oysters are produced, are low inerty systems highly sensitive to contaminants, which can also accelerate the emergence of epidemics/epizootics and zoonotic diseases in marine ecosystems. Among them, copper is a widespread pollutant that acts as a major selective pressure influencing microorganism survival and evolution as it can be deadly for many bacteria. Vibrio aestuarianus subsp. francensis is an emerging pathogen that threatens European aquaculture since 2011. Recent work revealed that this bacterium is an oyster-restricted specialized pathogen. The IHPE laboratory has evidenced that an intimate relationship between virulence and copper resistance conferred by a pathogenicity island could be key in the adaptation of the subspecies to the oyster host. This proposal aims to evaluate the role of copper resistance in V. aestuarianus francensis adaptation to oyster, and to unveil the copper resistance molecular pathways underlying this key phenotype and infection outcome. Specifically, we will address the following questions: -Is copper resistance required for V. aestuarianus adaptation and virulence to its host? -What is the diversity of V. aestuarianus copper resistance mechanisms? -Does accumulated copper in oyster have an impact in the host-pathogen outcome? By investigating resistance to copper and virulence as interlinked phenotypes of pathogens and its impact on oyster immunity, we will bring knowledge on the way copper influences the pathogens´dynamics, driving their evolution and specialization in marine ecosystems, but also modulating host-pathogen interactions. Ultimately, the project should help shellfish farmers and policy-makers mitigate the effects of anthropogenic pollution on aquaculture services.

Keywords: emerging pathogens,oyster disease,copper,copper pathogenicity island,aquaculture,infection,vibrio aestuarianus,crassostrea gigas,pathogenesis,host pathogen interactions,niche adaptation
Removing non-CO2 greenhouse gas emissions to support ambitious climate transitions (REPAIR)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Energy
Destination: Cross-sectoral solutions for the climate transition
Action type: Research and Innovation actions
Countries involved: Sweden,Norway,Netherlands,Poland,Finland,Italy,Spain
Call: Technologies for non- CO2 greenhouse gases removal (HORIZON-CL5-2021-D2-01, 2021)
Start date: 2022-10-01
End date: 2026-09-30
Duration (months): 48.0
Total project cost (EUR): 2996941.25
EU funding (EUR): 2996941.25
Participants: 9
Project status: SIGNED

Non-CO2 greenhouse gases are responsible for 28% of total anthropogenic emissions, of which CH4 (16%) and N2O (6%) are major contributors. These gases are hard to abate due to their diverse and inherently distributed sources (with concentration <1%-vol), for example the agricultural sector (livestock and farming), which is the main source of anthropogenic CH4 emissions. Moreover, their very low concentrations in the atmosphere (ppb or ppm level) make the recovery particularly challenging. However, mitigating these gases can significantly accelerate the transition towards a net-zero greenhouse gas EU economy by 2050, and achieve sustainable negative emissions thereafter. In this context, REPAIR will develop first-of-its kind technological proof of concept to remove non-CO2 gases like CH4 and N2O from diluted sources, including from the atmosphere. Two process routes are proposed: (i) capture, concentration and storage/conversion (ii) direct catalytic conversion. The proposed processes can be easily integrated with direct air capture and storage and/or use of CO2, thereby removing multiple greenhouse gases (CH4, N2O and CO2) in a single system with lower energy and cost. The potential of the technologies developed in the REPAIR project will be evaluated through (i) techno-economic analysis (ii) scenario-based assessment to evaluate impact on climate (iii) impact case studies in agricultural and farming sector. Results will enable making decisions about upscaling of the technology in agricultural farms by 2035 in addition to increasing knowledge about plausibility of removing non-CO2 gases from diluted sources. It will also help the European Commission to make informed decisions about regulations for non-CO2 greenhouse gas emissions from 2030 as indicated in the "Fit for 55" plan. The project consortium has expertise and experience to develop emerging and break-through technologies with high potential to achieve climate neutrality and create socio-economic impact.

Keywords: removing non co2 greenhouse gas emissions material development process design and optimization techno economics integrated assessment modelling stakeholder and end user interaction
CONTRACT: Conformal Calibration for Reliable AI-Based Wireless Communications (CONTRACT)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Systems and Communication Engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: United Kingdom
Call: ERC ADVANCED GRANTS (ERC-2024-ADG, 2024)
Start date: 2026-02-01
End date: 2031-01-31
Duration (months): 60.0
Total project cost (EUR): 2489890.0
EU funding (EUR): 2489890.0
Participants: 1
Project status: SIGNED

CONTRACT sets out to investigate a novel, theoretically principled, framework for the reliable deployment of artificial intelligence (AI)-based black-box models in wireless systems. Given the highly non-deterministic patterns of traffic and connectivity conditions, AI is currently viewed as an essential technology to ensure the support of communication services with widely heterogeneous performance requirements, ranging from cloud gaming to Industry 4.0. However, AI ``apps'' are, by and large, black boxes, whose introduction within the larger wireless network raises critical concerns about reliability. These concerns are not addressed by the vast literature on AI for wireless systems, which adopts a standard ``train-and-deploy'' best-effort approach. The main goal of CONTRACT is to endow for the first time AI-based wireless deployments with formal reliability guarantees. To this end, CONTRACT will introduce novel methodologies for: (i) the offline calibration of pre-trained AI apps via hyperparameter optimization prior to deployment; and (ii) the online run-time monitoring of key performance indicators and conflicts among simultaneously deployed apps. In CONTRACT, hyperparameter optimization and online monitoring will leverage contextual information describing traffic and connectivity conditions, as well as synthetic data from a digital twin, i.e., a simulator, of the wireless network. The research will build on conformal prediction, a statistical framework for assumption-free calibration, and on prediction-powered inference as a mechanism for the reliable integration of synthetic data. This project will lead to a reconsideration of the role of AI in the engineering of wireless networks from a potential reliability concern to a dependable part of the system.

Keywords: machine learning,statistics,information theory,conformal prediction
Development of life changing drugs for patients suffering from severe and fatal neurological disorders (RespirOndine)

Framework: Horizon Europe — Innovative Europe
Programme: European innovation ecosystems
Theme: Elevating the scalability potential of European business
Destination: Elevating the scalability potential of European business
Action type: Coordination and support actions
Countries involved: France
Call: Women TechEU (HORIZON-EIE-2022-SCALEUP-02, 2022)
Start date: 2023-07-01
End date: 2023-12-31
Duration (months): 6.0
Total project cost (EUR): 107142.86
EU funding (EUR): 75000.0
Participants: 1
Project status: CLOSED

AtmosR is a start-up whose mission is to develop innovative therapeutic solutions for patients suffering from severe and often fatal disorders of the central nervous system. Our company has established a technology in order to develop treatments for aggregate pathologies (such as ALS, Kennedy disease, Multisystem Atrophy, Parkinson, Huntington...) which represent a major health problem considering the high number of patients worldwide and the high unmet medical need. The first disorder targeted by AtmosR is Congenital Central Hypoventilation Syndrome (CCHS), a rare genetic syndrome which presents as its main symptom severe periods of hypoventilation. Patients are kept alive thanks to mechanical ventilation administered through a tracheostomy. Our goal is to develop a drug that will be life changing for patients and their families, liberating them from the machine, lifting the vital risk and allowing them to live independently. Our team consists of multidisciplinary profiles with experience in both drug development, particularly in the field of rare diseases, and in business management. As a spin-off of the french CCHS patient organization, we work in close cooperation with the international academic experts in CCHS, especially in France, Italy and Israël. We have identified a Hit compound ATS-003 that is active in both in vitro and in vivo CCHS robust models and we have optimized the compound thanks to a chemistry program in order to improve its efficiency and lower its toxicity for a better long term use tolerance. We are starting regulatory preclinical work in 2023 with this new Lead compound and have planned the first clinical trials by mid 2025 and an early drug access for patients in 2027. In addition to CCHS, we have identified several disorders with similar protein aggregation mechanisms. We plan to test and develop our Lead compound for other more common disorders and the purpose of this project is to idententify the most promising one for our Lead.

Keywords: neurological,disorder,drug,treatment,innovation,life changing,transformativ
On-chip tunable perovskite laser in the visible/near-infrared range (PEROTUNE)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Belgium
Call: ERC PROOF OF CONCEPT GRANTS (ERC-2024-POC, 2024)
Start date: 2025-05-01
End date: 2026-10-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: SIGNED

The availability of a tunable laser source in the visible and near-infrared (NIR) range is crucial for a variety of high-impact applications, such as frequency-modulated continuous wave LiDAR, optical coherence tomography, quantum photonics, and molecular spectroscopy. Despite the demand, current solutions for tunable lasers in these wavelength ranges remain limited, both in terms of availability and performance. Metal halide perovskite thin films are emerging as highly promising materials for such applications due to their exceptional optical properties, ease of processing, and compatibility with a wide range of substrates and photonic platforms. In PEROTUNE, we aim to demonstrate a mode-hop free (MHF) tunable laser by leveraging the unique properties of perovskite materials combined with innovative design strategies to enable continuous tuning without mode hopping. This approach capitalizes on the tunability and high optical gain of perovskites in the visible/NIR spectrum, addressing current limitations in laser source technology. By adopting advanced integration techniques, the proposed design will deliver compact, efficient, and versatile laser sources suitable for a wide range of applications. In particular, this breakthrough innovation has the potential to impact fields ranging from medical diagnostics and environmental monitoring to advanced manufacturing and telecommunications, opening new doors for next generation photonic devices
Foundation Model-Based Biomarker Platform for Radiology and Clinical Trials (FoundRa)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: France
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 24.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

The FoundRa project is based on 2 challenges: (1) Due to aging and population growth, there is an increase in pathologies that require radiology, from diagnosis to follow-up. (2) The ambition to make personalized medicine the standard of the future requires all kinds of biomarkers. Raidium is an agile, young and ambitious French company, born from the mission of the co-founders to accelerate the application of precision medicine and relieve radiologists from their enormous workload. Raidium delivers the first scalable interactive AI platform for radiology, supporting radiologists in their work, enabling a broader group of clinicians to benefit from radiology insights, and making clinical trials faster and more cost-effective. The innovation is a multimodal foundation model (FM) that uses self-supervised learning based on unlabeled data, creating scalable biomarkers; unlike current offerings where biomarker-generating AI can only target one segment, due to the time- and cost-consuming effort of supervised learning based on manually labeled data. The human-centric platform offers an intelligent interactive and intuitive human-machine interface that can be trained by the radiologist, leveraging their experience while performing automatic segmentation, annotation and analytical tasks, providing reports and decision support. Radium's beachhead market is to be an AI-enabled contract research organization for pharmaceutical companies, providing strategic AI-generated biomarkers. Radium's ultimate market is to provide an AI radiology platform as a Software as a Service (SaaS) to radiologists and clinical researchers in hospitals and pharma. With the support from EIC, we will train our FM, integrate it into our platform, and accelerate the creation of AI-based biomarkers. This initiative aims to revolutionize and bring about significant advances in the fields of precision medicine in respect to medical practice and clinical trials.

Keywords: multimodal foundation model,precision medicine,human machine interface,self supervised learning,few shot learning,zero shot learning,human centric ai,clinical trials,nash,liver diseases