Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Integrated simulations of active emulsions in complex environments (EmulSim)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Condensed Matter Physics
Panel description: Structure, electronic properties, fluids, nanosciences, biological physics
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2021-COG, 2021)
Start date: 2022-10-01
End date: 2027-09-30
Duration (months): 60.0
Total project cost (EUR): 1998334.0
EU funding (EUR): 1998334.0
Participants: 1
Project status: SIGNED

Biological cells consist of a myriad of interacting biomolecules that collectively arrange in stable structures. For example, molecules undergo phase separation to form so-called biomolecular condensates. We now know that malfunctioning condensates can cause diseases like Alzheimer’s, Parkinson’s, and cancer. Yet, we do not understand how condensates become malfunctioning and how healthy cells control them. Some challenges in understanding condensate dynamics are that cells are heterogeneous, have complex material properties, and exhibit significant thermal fluctuations. Biological cells are also alive and use fuel molecules to control processes actively. I recently showed that active chemical reactions could generally affect the dynamics of droplets. However, it is unclear how such active droplets behave in the complex environments inside cells. EmulSim will study how cells control biomolecular condensates and provide a novel integrated simulation method incorporating relevant processes on all length scales. On the scale of individual droplets, I will investigate the influence of driven reactions and elastic material properties of droplets. On the cellular scale, I will study the effect of the elastic cytoskeleton and the presence of multiple compartments. For each of these processes, I will derive experimentally verified models using examples of relevant biological processes, including cell division, chromatin organization, and signaling. Combining the physical theories for these critical processes will culminate in an agent-based model describing a collection of droplets, ultimately also including number fluctuations. This novel simulation framework will model biomolecular condensates in their cellular environment. Taken together, EmulSim will propel our understanding of biomolecular condensates and lay the ground for the development of novel therapies in medicine.

Keywords: soft matter,phase separation,theory,multi scale simulation,biomolecular condensates,cell biology
Direct in utero engineering of mouse models (LIMITLESS)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator 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: Sweden
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-05-01
End date: 2030-04-30
Duration (months): 60.0
Total project cost (EUR): 2265000.0
EU funding (EUR): 2265000.0
Participants: 1
Project status: SIGNED

Mouse models are a gold standard for life sciences research, spanning developmental biology, cancer studies, and pre-clinical testing, but they also have important limitations. Mouse colony maintenance is expensive, and the large colonies needed are ethically problematic. Approaches aiming for cell-type specific manipulations can be confounded by leaky promoters, off-target/unknown promoter expression, endogenous Cre sites, and Cre toxicity. Finally, mouse strains generated in different inbred genetic backgrounds yield confounding results when interbred, or necessitate extensive back-crossing, and again - large usage of mice. An alternative strategy to generate mouse models, circumventing these issues, is direly needed. To solve this problem for the mouse nervous system, we previously developed neural plate targeting with in utero nano-injection (NEPTUNE). NEPTUNE targets 95% of cells in the brain, can recapitulate established mouse models, and can be used flexibly for cell-type specific manipulations. In LIMITLESS, my lab will leverage our expertise in ultra-high titer viral production, developmental biology, and technology development to go beyond the state of the art and develop a technology for whole-embryo editing in utero. We will combine this technology with next generation single cell lineage tracing, to resolve the “family tree” of all cell types in developing embryos, providing both fundamental new knowledge and information that is leverageable for further development of the technique. In sum, my lab will go develop a much-needed technology for whole embryo genetic manipulation, opening the door to limitless new types of experiments. Direct in utero whole-embryo gene editing would accelerate life sciences research, reduce the financial and ethical costs of animal work, and enable experiments currently beyond reach with existing technology.

Keywords: mouse models,transgenics,lineage tracing
The Origins of Human Rhythm (TOHR)

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: Italy
Call: ERC STARTING GRANTS (ERC-2021-STG, 2021)
Start date: 2023-06-01
End date: 2028-05-31
Duration (months): 60.0
Total project cost (EUR): 1496294.0
EU funding (EUR): 1496294.0
Participants: 2
Project status: SIGNED

Humans are particularly rhythmic animals. Why did the human sense of rhythm develop? Many hypotheses try to explain the origins of our acoustic rhythm capacities, but few are empirically tested, compared, and comparatively investigated. This project searches for the evolutionary roots of human rhythmicity, breaking new ground through three concerted approaches. First, I zoom in on key rhythmic properties: isochrony, an even occurrence of events in time, and meter, a relative accentuation of events. Second, I compare hypotheses on rhythm origins, selecting the most relevant ones to music and speech and testing them against each other. Third, I target rhythm precursors in other species as predicted by these alternative hypotheses. I test four hypotheses, which propose that 1) gait or 2) breathing control, and the ability to 3) learn new sounds or 4) sing in a chorus are evolutionary precursors to human rhythm. I will use different measures including behavior, electrophysiology, gait tracking, breathing, and computational modeling to test whether the four features above predict rhythmic capacities. Comparative animal work is needed to test whether similar evolutionary pressures lead to similar rhythmic traits. I will collect data from humans and four more species. I will test seals, displaying vocal learning, and porpoises; both mammals have developed breathing control. I will also test siamangs, displaying rhythmic locomotion, and indris; both primates naturally sing in choruses, a rare trait in non-human mammals. Finding rhythm in other species will provide a test bench to reconstruct the origins of human rhythm. Resting on my background in bioacoustics and mathematics, the project expands in new challenging directions, such as neurophysiology of marine mammals, automated gait analyses, and biomusicology. In brief, I will show which species have rhythm, and why humans evolved to be such chatty, rhythmic creatures.

Keywords: evolution of music biomusicology evolution of speech timing comparative cognition animal communication
Investigation of endocrine-disrupting chemicals as contributors to progression of metabolic dysfunction-associated steatotic liver disease (EDC-MASLD)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Living and working in a health promoting environment
Action type: Research and Innovation actions
Countries involved: Sweden,Netherlands,Germany,Italy,Norway,Spain,France,Finland,United Kingdom,Serbia
Call: Health impacts of endocrine-disrupting chemicals: bridging science-policy gaps by addressing persistent scientific uncertainties (HORIZON-HLTH-2023-ENVHLTH-02, 2023)
Start date: 2024-01-01
End date: 2028-12-31
Duration (months): 60.0
Total project cost (EUR): 7053942.75
EU funding (EUR): 7053942.75
Participants: 15
Project status: SIGNED

MASLD is the condition of excessive accumulation of liver fat unrelated to alcohol intake, ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH). With a 25% prevalence in the general population, MASLD is currently the most common liver disease, and a major healthcare and economic burden. While hyperlipidaemia, obesity and insulin resistance are the major risk factors for MASLD and contribute to its rising prevalence, growing evidence suggests that exposure to endocrine-disrupting chemicals (EDCs) can initiate and/or cause progression of MASLD. EDC-MASLD will focus on investigating the impact of environmental exposure to EDCs on the internal exposome (metabolome, gut microbiome, epigenome, proteome, immunome) and degree of liver damage in MASLD in prospective study settings, with a focus on the period of transition to progressive stages of MASLD. EDC-MASLD is particularly focused on interactions between EDC exposure, sex, genotype, diet, socioeconomic and lifestyle factors, via the data and biosamples available in the unique European NAFLD Registry, comprising over 9,000 patients with histologically characterised MASLD. EDC exposure studies will be performed in murine models of MASLD, zebrafish models, and human 2D/3D in vitro models, with an aim to understand respective mechanisms-of-action and to develop novel EDC screening tools. The EDC-MASLD consortium has diverse and complementary expertise in the domains of hepatology, endocrinology, toxicology, exposome research, metabolomics, systems biology, environmental economics, and communications & technology research, with respective PIs being global leaders in their fields. Taken together, EDC-MASLD will significantly contribute to the actions centred on identification and mechanistic assessment of impact of EDCs, strategies to monitor and reduce exposure, and regulatory actions that could better protect human and environmental health.

Keywords: nafld,pfas,exposome,liver,lipids,bile acids
Power System Simulator based on Physics-Informed Neural Networks (PINNSim)

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: Denmark,Cyprus
Call: ERC PROOF OF CONCEPT GRANTS (ERC-2025-POC, 2025)
Start date: 2026-01-01
End date: 2027-06-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 2
Project status: SIGNED

This proposal puts forward a first-of-its-kind power system dynamics simulator based on neural networks: PINNSim. PINNSim aims to deliver a highly modular and scalable tool that can be up to 100x faster than any commercial power system simulator. This means that PINNSim can perform a power system stability assessment in 30 minutes instead of 2 days. We witness a dramatic shift from few large scale generators to millions of converter-based resources, such as solar, wind, batteries, and electric vehicles. Capturing the dynamic behavior of such a system is no longer possible with the conventional approximations. In case of fault, phenomena propagate much faster and an ElectroMagnetic Transient (EMT) simulation is necessary to accurately capture them. However, EMT is slow and computationally intensive. Uncertainty from solar and wind and the increased number of components requires the assessment of millions of critical scenarios so that power system operators eliminate blackout risk, and manufacturers design appropriate controllers for the safe operation of their equipment. PINNSim leverages physics-informed machine learning and GPU acceleration to model power system components. Its key novelty lies in the method it interconnects individual neural networks to form a “system of neural networks” that performs simulations at much higher speeds. Through this funding, we aim to scale PINNSim to handle larger, more complex power systems and incorporate a user interface, creating a user-friendly simulator capable of addressing a wide range of power system operation challenges. Our goal is to create a tool that will disrupt the power system simulation software landscape. We envision a library of component models based on neural networks, which can then be used in a plug’n’play fashion in PINNSim, similar to conventional simulators. If successful, PINNSim can naturally extend to almost any non-linear dynamic system such as robotics and biological systems.

Keywords: physics informed neural networks,physics informed machine learning,power systems,electromagnetic transient simulations,power system dynamics,renewable energy,electric grids
goCAD: AI-Powered Digital Transformation for Europe’s Job Shop Manufacturing (EMOS-ProductionAI)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Germany
Call: EIC Accelerator 2025 - Short application (HORIZON-EIC-2025-ACCELERATOR-01, 2025)
Duration (months): 24.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: CLOSED

goCAD GmbH, a German deep-tech startup, offers a SaaS platform transforming manufacturing quotation and process planning for European SMEs. Our 'Part Intelligence AI', built on a proprietary AI foundation model. This Explainable AI (XAI) system directly analyzes 3D component topology for precise manufacturing feature recognition and process planning. It generates instant, highly accurate cost estimates tailored to each manufacturer’s machinery and cost models. The platform further automates entire pre-production workflows, including detailed working plans, precise cycle times, CNC-ready programs, and integrates a CO2 footprint calculator to support EU Green Deal objectives and emerging carbon accounting requirements. Europe's manufacturing SMEs, the backbone of a €2.5 trillion GDP sector employing 30 million people, face global competition and a need for digitalization. Manual quoting is slow and inefficient. goCAD reduces turnaround from days to minutes, doubles win rates, and empowers SMEs with independent e-commerce portals. We seek €2.5M in grant funding and €2.0M in equity from the EIC Accelerator. The grant will de-risk high-innovation activities, scaling our product from TRL 6–7 to TRL 8 via secure microservices, further improving next-gen Predictive and Explainable AI, and expanding into new manufacturing domains. The equity will drive EU-wide commercialization through sales expansion, product localization, customer onboarding, and operational scale-up. This project advances the EU’s Digital and Green transitions, strengthens SME competitiveness, safeguards industrial sovereignty through a federated European Manufacturing Orchestration System (EMOS-ProductionAI), and contributes to UN SDGs 8, 9, 12, and 13.

Keywords: digital manufacturing cad cam ai jobshops
Monitoring of stroke patients with 3D ultrasound localization microscopy (StrokeMonitor)

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: France
Call: ERC PROOF OF CONCEPT GRANTS2 (ERC-2022-POC2, 2022)
Start date: 2023-02-01
End date: 2024-07-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 2
Project status: CLOSED

The ERC Cog ResolveStroke has led to the development of a new imaging device, based on super-resolution ultrasound, which can assess ischemic and hemorrhagic stroke through the observation of the smallest blood vessels which are invisible to other medical imaging modalities. This StrokeScanner is currently being demonstrated in a large models before being applied to human studies at the end of the project. Its remarkable results have led to the creation of a startup (Resolve Stroke) which conceives a portable and 3D super-resolution ultrasound scanner to improve access to neuroimaging for stroke patients. In particular, there is a dire need to monitor the cerebral blood flows at the patient’s bedside after the acute phase. Delayed cerebral ischemia arises in a third of all patients suffering from subarachnoid hemorrhage (about 800 000 cases worldwide per year). Transcranial doppler is used to explore large vessel circulation but is blind to fine vascular alterations. We believe that ultrasound super resolution could bring a new diagnostic tool to help patients and physicians, with a resolution and sensitivity comparable to CT Angiography on a device smaller than a carry-on luggage. The goal of the ERC POC StrokeMonitor is to establish the performance and usefulness of this approach to monitor Delayed Cerebral Ischemia. The demonstration will be performed both in models and in human patients. A model of subarachnoid hemorrhage will be imaged over several days to determine the dynamic of the microcirculation alterations. A clinically-validated StrokeScanner will then be tested on SAH patients at CHU de Caen to identify biomarkers of delayed cerebral ischemia in hemorrhagic stroke patients. Through this ERC POC StrokeMonitor, we will extend the applicability of the Strokescanner in neurovascular units in hospitals to help patients’ follow-up and generate stronger proof of ultrasound super-resolution for neuroimaging
Large scalE Integration demonstrator of hybrid electrical Architecture (LEIA)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Public-private partnerships
Destination: Clean Aviation
Action type: Innovation actions
Partnership: CLEAN-AVIATION (JU-JTI)
Countries involved: Spain,Ireland,United Kingdom,Germany,Italy,France,Austria,Belgium,Poland,Netherlands,United States
Call: Ground Test Demonstration up to TRL5 of On-Board NPE Systems Architecture for SMR Aircraft (HORIZON-JU-Clean-Aviation-2025-01, 2025)
Start date: 2025-12-01
End date: 2027-12-31
Duration (months): 25.0
Total project cost (EUR): 49357143.44
EU funding (EUR): 35000000.0
Participants: 28
Project status: SIGNED

LEIA (Large scalE Integration demonstrator of hybrid electrical Architecture) is fundamental in the context of Clean Aviation's strategic goals to reduce greenhouse-gases emissions and advance green aviation technologies. This challenge is often associated with propulsion technologies or disruptive wing configurations, but it is not limited to that, and both pathways are enabled by novel system technologies and architectures. LEIA is essential for preparing the future short-medium-range aircraft more/hybrid electric non-propulsive energy architecture. It aims at designing and integrating non-propulsive electrical systems to enable an increased engine off-take efficiency together with a more flexible energy management, while minimizing the overall system sizing. To enable the integration of a high-performance, certifiable, and scalable non-propulsive energy system contributing to Clean Aviation’s sustainability and performance targets, the project will: - select and validate a future-focused more electric/hybrid electric non-propulsive energy architecture, - define comprehensive functional and interface specifications, - develop advanced energy and thermal management strategies, - establish a clear integration strategy, - demonstrate TRL5 for an integrated energy provision system level, - provide a roadmap towards TRL6 for the end-to-end electrical system architecture, - prepare a certification and industrialization roadmap, - advance certification readiness of critical technologies by achieving CRL4 and identifying a pathway to CRL6. A key project objective is to demonstrate, by a successful TRL5 review in 2027, non-propulsive energy architecture for a short-medium-range more/hybrid electric aircraft concept, including the system's integration into the broader aircraft architecture. LEIA is therefore a core enabler to deliver at TRL5 and CRL4 a consistent package of key technologies for a next generation more environmentally-friendly aircraft.

Keywords: designing short medium range aircraft more hybrid electric non propulsive systems efficient management of on board energies from generation to distribution to the final consumer systems
Artificial intelligence for synthetic functional genomics of blood (AI4SYN)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Integrative B iology : from Genes and Genomes to S ystems
Panel description: For all organis ms: Genetics, epigenetics, genomics  and other ‘omics studies , bioinformatics, systems biology , genetic diseases , gene editing, innovative methods and modelling,  ‘omics for personalised  medicine
Countries involved: Spain
Call: ERC STARTING GRANTS (ERC-2021-STG, 2021)
Start date: 2022-09-01
End date: 2027-08-31
Duration (months): 60.0
Total project cost (EUR): 1499653.0
EU funding (EUR): 1499653.0
Participants: 1
Project status: SIGNED

Our abilities to predict and engineer complex biological systems are in their infancy. In the context of gene regulation, we cannot design artificial promoters with specificity to arbitrary cell states, and we cannot arbitrarily trans- and de-differentiate somatic cells, although such abilities would be of high biotechnological and biomedical value. To achieve these ambitious goals, we require quantitative, predictive models of gene regulatory elements (GREs) and gene regulatory networks (GRNs), respectively. Here I propose that the combination of deep learning and single-cell genetic screens is ideally suited to obtain such models, and, in particular, the amounts of highly informative data required for their training. Working with an ex vivo model of hematopoietic stem cell differentiation, we will first screen the activity of hundreds of thousands of synthetic GREs throughout the hematopoietic differentiation landscape. Thereby, we will obtain models of cell type specific GRE activity that can predict new, synthetic GREs with activity in any cell state of interest. Second, we will screen hundreds of thousands of combinatorial GRN perturbations and their effect on cell state. Thereby, we will derive models of GRNs that can predict combinatorial perturbation strategies to achieve arbitrary de- or trans-differentiation events. In sum, work on this project will yield a quantitative model of gene regulation in hematopoiesis at various scales of complexity while introducing a novel, AI-guided concept for biological engineering.

Keywords: single cell genomics,single cell genetic screens,machine learning