Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Automated canceR-on-A-CHip orgaN-specific metastatIc spreaD (ARACHNID)

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: Italy
Call: ERC PROOF OF CONCEPT GRANTS (ERC-2023-POC, 2023)
Start date: 2024-07-01
End date: 2025-12-31
Duration (months): 18.0
Total project cost (EUR): 160714.29
EU funding (EUR): 150000.0
Participants: 2
Project status: SIGNED

Despite the improvements in cancer treatments, diagnostic tools and prevention/early detection strategies, cancer is still a major public health burden as one of the 6 leading causes of death worldwide. In 2020, 90% of the 10 million deaths registered out of 19.3 million new cancer diagnoses were associated not with primary tumors but with the secondary ones generated by the metastatic process. The complex time-dependent chain of events and cascades of biophysical and biochemical factors regulating tumor metastasis cannot be replicated using conventional in vitro cell models (such as transwell invasion and scratch/wound healing assays) nor in vivo animal models. The scientific and medical communities are striving to better understand the steps of metastatic spreading to devise strategies to stop its occurrence, especially in pediatric oncology, as in the case of Neuroblastoma, the most common and difficult to treat among tumors of preschool age (15% of pediatric oncology deaths). To solve these limitations we propose ARACHNID, a unique, multiplexed, automated, and increased-throughput multi-organ on a-chip platform conceived around the complex process of cancer metastatic spread. The project's potential for breakthrough innovation resides in its unique capabilities, promising to accelerate research, reduce costs, and contribute to the development of more effective cancer treatments. The ARACHNID project aims to explore and prove the technical-commercial potential of our proprietary tumor-metastasis-on-a-chip (TMOC) platform, starting from pediatric tumors and extending the application to adult cancers, involving Biogenera, biotechnological SME operating the pharma NB domain, as a testbed and early adopter.
EIT Cross-KIC Strategic Access to Finance (EIT_XKIC_A2F)

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: France,Germany,Belgium,Spain,Netherlands
Call: EIT Cross-KIC Strategic Access to Finance (HORIZON-EIT-2023-2025-KIC, 2023)
Start date: 2023-01-01
End date: 2025-12-31
Duration (months): 36.0
Total project cost (EUR): 2552666.0
EU funding (EUR): 2552666.0
Participants: 10
Project status: SIGNED

Developing synergies of the EIT community with EIC and EIF to facilitate investments (Access to Finance) for the KICs supported ventures (startups/scaleups) & innovation projects, and that also contribute to the KICs’ financial sustainability and diversification of revenues from RoI mechanisms/Equity.

Keywords: private investment financial engineering corporate financing financial and investment management banking,corporate finance,accounting startups
Advancing nucleosynthesis predictions with modern supernova simulations (NUC4SIM)

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: Physics
Countries involved: Germany
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2022-10-01
End date: 2024-09-30
Duration (months): 24.0
Total project cost (EUR): 189687.36
EU funding (EUR): 189687.36
Participants: 1
Project status: CLOSED

Core-collapse supernova (CCSN) explosions mark the end of the life of stars heavier than 10 times the mass of our sun, they play a crucial role for our understanding of the chemical composition of the universe and they are ideal laboratories for effects of neutrino and particle physics. Current research in astrophysics, astronomy and cosmochemistry that requires theoretical CCSN models still, however, relies predominantly on one-dimensional, i.e., spherically symmetric parameterized calculations. This project aims at advancing the state-of-the-art by calculating the composition of CCSN material based on the most recent, first-principles 3D simulations and by providing the results to the community in accordance with FAIR data management principles. The researcher's background in nuclear and neutrino physics will also allow him to study the implications of uniquely multi-dimensional asymmetries in the neutrino emission and the consequences of neutrino flavor conversions, a quantum effect that changes the particles' spectra, for nucleosynthesis, both of which have never been explored and may lead to observational signatures. To achieve the goals, a new and innovative framework for nucleosynthesis calculations at the Max-Planck Institute for Astrophysics in Garching will be developed, based on an open-source reaction network code, which the researcher has contributed to and that he will apply to unique cutting-edge models. The fellow will obtain in-depth knowledge about supernovae and learn state-of-the-art techniques from the world-class team of Prof. Janka and apply them. He will broaden the scope of his work, complemented by a career development plan, training courses and coaching as well as detailed dissemination and public outreach plans to maximize the impact of the project's outcome. The completion of the project will allow the fellow to become a mature and independent scientist, well-recognized in his field of research.

Keywords: nucleosynthesis,neutrinos,neutrino oscillations,core collapse supernovae,simulations,radioisotopes
Highly Efficient Super Critical ZERO eMission Energy System (HERMES)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Energy
Destination: Sustainable, secure and competitive energy supply
Action type: Research and Innovation actions
Countries involved: Netherlands,Greece,Germany,Switzerland,United Kingdom,France,Poland
Call: Next generation of renewable energy technologies (HORIZON-CL5-2021-D3-03, 2021)
Start date: 2022-11-01
End date: 2026-04-30
Duration (months): 42.0
Total project cost (EUR): 2594660.0
EU funding (EUR): 2594660.0
Participants: 12
Project status: SIGNED

Wind and sun will be central energy sources of a climate neutral Europe 2050, bringing with them the need to balance weather dependent differences between supply and load. Conventional gas turbines can fulfill this task also for longer periods even well as they can stabilize the grid with their capability of quick start/stop. However, their efficiency is limited and – even if burning climate neutral hydrocarbons – they still produce local emissions. HERMES overcomes these limitations and advances gas turbine technology to the future-proof level by creating a reliable, flexible, zero-emission solution for energy supply with long term impact at EU level. HERMES develops and assesses the first highly efficient closed-loop supercritical zero emission energy system. It is based on directly fired supercritical gas turbine engine operating on locally synthesized renewable liquid and gaseous fuels (e.g. methanol or hydrogen) coupled with decentralized carbon capture utilization and storage (CCUS). The carrier medium is highly dense supercritical carbon dioxide or xenon demanding less compression power. Therefore, and because of operating at high pressure conditions (above 150 bar), the system achieves significantly higher efficiency (above 65%) than today’s gas turbines. By utilizing pure oxygen for fuel oxidation, and by capturing bulky flow of exhaust products (H2O and/or CO2) and reusing them for fuel synthesis, the system produces virtually no pollutants. A detailed assessment of the HERMES approach will be done using experimental and computational approaches and dynamic simulation tools including digital twins and machine learning. The 36-month project will be realized by an 11-partner consortium including 3 SMEs with expertise in renewable energy, combustion, techno-economics and socio-political science. Hermes will pave the way to a major breakthrough in the understanding of fundamentals of combustion in supercritical fluids with zero emission of any pollutants.

Keywords: zero emission closed loop renewable system,supercritical fluids,high pressure gas turbines,decentralized fuel synthesis with ccus,techno economic,environmental,social,policy assessment
Property transformation of Grain Boundaries (ProGB)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Materials Engineering
Panel description: Advanced materials development: performance enhancement, modelling, large -scale preparation, modification, tailoring, optimisation, novel  and combined use of materials, etc.
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-07-01
End date: 2030-06-30
Duration (months): 60.0
Total project cost (EUR): 1995938.0
EU funding (EUR): 1995938.0
Participants: 1
Project status: SIGNED

Property transformation of grain boundaries (ProGB) is a challenge and a big opportunity. Besides being indispensable in many semiconductor compounds, grain boundaries (GBs) are found to be often detrimental in most bulk and thin-film solar cells limiting devices’ efficiency. This is because understanding how the detrimental properties can be intentionally transformed remains difficult and often impossible. Therefore, ProGB aims to understand and even transform the GBs properties on the nanoscale by employing a novel approach. This approach consists of three steps with three objectives. (1) It will explore the GBs' intrinsic properties and the properties transformation down to the nanoscale in semiconductor prototypes through a new platform specially developed for GB characterization. It will (2) understand the impact of GBs’ structure and stoichiometry on the electronic properties down to the nanoscale and (3) utilize the experimental evidence and the concepts gained to obtain high-performance photovoltaic and electronic devices. Finally, ProGB will employ a unique infrastructure that will be implemented and established in the PI’s team. It will apply atom probe tomography as a principal technique to determine the composition of GBs in Si (as a typical prototype material) and in AgBiS2 (as a novel material for ultrathin-film solar cell applications), combined with techniques to determine the materials’ electronic and structural properties on exactly the same position on the sample. In this way, ProGB can realize a true 1:1:1 correlation with unprecedented precision in material characterization. These experimental observations will be consolidated by theoretical simulations and device modeling. Last but not least, the outcome of ProGB will rescue thin-film technology with polycrystalline absorbers and will be of big benefit to the latest technologies such as tandem and ultrathin-film solar cells.
Direct on Sputum Sequencing to Interrupt Transmission of Rifampicin Resistant Tuberculosis (DiSrupT RR-TB)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Prevention,  Diagnosis and T reatment of Human Diseases
Panel description: Medical technologies  and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions , pharmacology, preventative  medicine, epidemiology and public health , digital medicine
Countries involved: Belgium
Call: ERC ADVANCED GRANTS (ERC-2024-ADG, 2024)
Start date: 2026-01-01
End date: 2030-12-31
Duration (months): 60.0
Total project cost (EUR): 2499855.0
EU funding (EUR): 2499855.0
Participants: 1
Project status: SIGNED

The DiSrupT RR-TB pragmatic cluster randomized trial (CRT) will tackle the ongoing public health threat of rifampicin-resistant tuberculosis (RR-TB) and prevent the emergence of bedaquiline-resistant tuberculosis (BDQR-TB) as a new public health crisis. The trial aims to evaluate an innovative all-in-1 solution for whole genome sequencing (WGS): the recently launched QIAseq xHYB Mtb assay for WGS directly on sputum (dWGS) in combination with Illumina sequencing and the novel digital MAGMA-MICK platform for automated analysis, interpretation, and communication of dWGS results to health care workers. The intervention aims to provide optimal treatment for all patients (precision medicine) and to reduce transmission of RR-TB in high-burden settings by breaking transmission chains in hotspots and superspreading events (precision public health). The trial will take place in KwaZulu-Natal, South Africa, and address four objectives to provide a holistic evaluation of the intervention's impact: (1) reduction in the recent transmission rate of RR-TB, (2) prevention of a rise in the proportion of cases of BDQR-TB that are due to transmission versus acquisition, (3) increase in timely initiation of effective treatment regimens for patients with BDQR-TB and (4) improved treatment outcomes of BDQR-TB. Data analysis will employ causal inference methodologies, including the difference-in-difference method for the cluster-level analyses (objectives 1 and 2), and inverse probability weighting for the individual-level analyses (objectives 3 and 4). The methodological rigor of the pragmatic CRT design will generate results with high internal and external validity, which is needed to inform policy and practice. If the intervention is shown to be effective and feasible, the trial will represent a paradigm shift in how genomic data can be utilised in public health interventions in low-resource countries and make a transformative contribution to infectious disease control efforts.

Keywords: global health,personalized medicine,tuberculosis
n-ary spintronics-based edge computing co-processor for artificial intelligence (MultiSpin.AI)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Pathfinder
Destination: Open to supporting projects in all areas of science, technology,...
Action type: EIC actions
Countries involved: Israel,Portugal,Belgium,Italy,Czechia
Call: EIC Pathfinder Open (HORIZON-EIC-2023-PATHFINDEROPEN-01, 2023)
Start date: 2024-02-01
End date: 2027-01-31
Duration (months): 36.0
Total project cost (EUR): 3143276.25
EU funding (EUR): 3143276.25
Participants: 7
Project status: SIGNED

The rise of technologies such as the Internet of Things (IoT), autonomous vehicles, smart cameras, etc. is generating lots of big data. The volume of data in 2022 was 97ZB and is doubling every 2-3 years. This is leading to unprecedented growth in energy consumption and costs needed for data processing. Sending raw data for remote processing on centralized nodes is limited in terms of speed and bandwidth, and even next-gen tech like 5G or 6G will be insufficient to cope with this growth. Processing data at the Edge, where it's generated, requires increasing power efficiency by several orders of magnitude. However, the use of general-purpose digital processors based on von Neumann architecture is limited, with optimization possibilities nearing natural limits. A new class of chips, neuromorphic hardware, is needed to execute AI algorithms like Deep Learning at high speed, low energy consumption, endurance, and scalability. MultiSpin.AI’s vision is to improve neuromorphic computing by increasing the energy efficiency and processing speed by at least three orders of magnitude over digital computing and >10x compared to the most advanced neuromorphic devices to reach an unparalleled 2,000 Tera operations per second per watt (TOPS/W). To achieve this, MultiSpin.AI will develop an AI co-processor based on a crossbar of multi-level magnetic tunnel junctions (M2TJ) cells/ n-ary state cells. The use of multi-level M2TJs reduces the number of cells, simplifies circuity, and reduces the number of digital-to-analog conversions (DAC) at the input of the crossbar, and analog-to-digital conversions at the crossbar output. The combined effect is realising much higher energy efficiency and faster AI inference at the Edge. This breakthrough will help provide a significant impact by enabling transformative applications like autonomous vehicles, robots, and medical devices and help strengthen strategic autonomy for the EU chips industry and reduce CO2 emissions from AI inference.

Keywords: neuromorphic computing,edge computing,magnetic memory,ai accelerator,ai co processor,artificial intelligence,internet of things,iot,machine learning,analog computing,neuromorphicspintronics
Efficient infinite-dimensional optimization over measures (OptInfinite)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: France
Call: ERC STARTING GRANTS (ERC-2025-STG, 2025)
Start date: 2025-10-01
End date: 2030-09-30
Duration (months): 60.0
Total project cost (EUR): 1499632.5
EU funding (EUR): 1499632.0
Participants: 1
Project status: SIGNED

Optimization over probability measures has become a powerful approach for solving complex problems that involve probabilistic modeling. Advanced by the PI and collaborators, it extends finite-dimensional optimization to the infinite-dimensional space of probability measures. This framework provides a princi- pled way to address in particular the task of sampling, that refers to the process of drawing samples from a complex probability distribution, either to approximate it or generate new data. In Bayesian machine learning for instance, we can model uncertainty of the predictions by sampling a model’s parameters. Similarly, in generative modeling, sampling is crucial for producing new data such as images or text. Existing methods struggle with complex measures, are difficult to evaluate, and are limited to Euclidean spaces, making them unsuitable for infinite-dimensional ones like functions or operators. Also, their lack of computational efficiency limits their use in sequential sampling tasks. My goal is to create a unified framework to design and evaluate efficient methods for sampling measures over general spaces. Central to my approach is the use of tools from optimal transport and information geometry, which will help compare measures and design optimization dynamics. OptInfinite will advance optimization over measures by addressing two key challenges: 1) developing optimization objectives and geometries suited to the space of measures over general (possibly-infinite-dimensional) spaces to design tractable schemes and metrics, and 2) learning to solve advanced optimization problems, such as sequences of optimization tasks. This framework will yield novel sampling methods, whose efficiency can be evaluated using optimization tools. It will also enable to compare measures and reveal where and how they are different. Ultimately, our work will provide a clear methodology and toolset applicable across multiple domains.

Keywords: bayesian inference methods,generative modeling,optimal transport,particle systems
Federated cybeR-physical infrastructure for ODD cOntinuity (FRODDO)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Mobility
Destination: Safe, Resilient Transport and Smart Mobility services for passengers and goods
Action type: Innovation actions
Partnership: CCAM (co-programmed)
Countries involved: Belgium,Greece,Slovenia,Italy,Türkiye,Finland,France,Luxembourg,Cyprus,Portugal
Call: Infrastructure-enabled solutions for improving the continuity or extension of Operational Design Domains (ODDs) (CCAM Partnership) (HORIZON-CL5-2023-D6-01, 2023)
Start date: 2024-06-01
End date: 2027-05-31
Duration (months): 36.0
Total project cost (EUR): 7683937.5
EU funding (EUR): 5994087.5
Participants: 19
Project status: SIGNED

The operational context is the cornerstone to ensure performance and safety of CCAM. The ODD, by design, defines the operating environment for which a system is designed for. On the other hand, Authorities and Road Operators are responsible for operating the PDI with a variety of vehicles and systems with limited knowledge on the diverse ODD specifications. To answer the question of how safe is a CCAM service, one should not only address the ODD used for shaping the functional boundaries of CCAM (top down), but also the infrastructure, system related, safe and secure communications related and conditions (traffic, weather, hazards) related aspects of the road environment these systems will operate (bottom up). The grande challenge is to design broader ODDs that allow for cooperation with the PDI in a safe system design framework; the industry cannot unilaterally develop and operate sustainable and robust ODDs without the feedback from Authorities and Operators. Future ODDs should be designed with many redundancies (fail safe design) to allow for increased tolerance to vehicle- and context-specific capabilities and human errors and cooperate with physical and digital road infrastructure to boost proactive safety; Seamless, safe and secure physical and digital environments must coexist and collaborate to allow for the appropriate levels of data, information and decisions flow. FRODDO’s vision is a future of robust, safe, secure and seamless connectivity and automation that can adapt to physical, technological and social challenges and support user centric mobility and development. FRODDO’s overarching aim is to develop and test a complete suite of methods and tools based on the principles of safe systems design in a federated DT environment leveraging advanced sensing, ML, hybrid AI and simulation to account for increasing adaptability and sustainability of ODDs to complex and dynamically changing road contexts and allow for improved management of CCAM-enabled PDI.

Keywords: digital twins odd continuity complex vehicle interactions