Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Flexible Statistical Inference (FLEX)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: Netherlands
Call: ERC ADVANCED GRANTS (ERC-2023-ADG, 2023)
Start date: 2024-11-01
End date: 2029-10-31
Duration (months): 60.0
Total project cost (EUR): 2499461.0
EU funding (EUR): 2499461.0
Participants: 1
Project status: SIGNED

Most statistical methods require that all aspects of data collection and inference are determined in advance, independently of the data. These include when to stop collecting data, what decisions can be made (e.g. accept/reject hypothesis, classify new point) and how to measure their quality (e.g. loss function/significance level). This is wildly at odds with the flexibility required in practice! It makes it impossible to achieve error control in meta-analyses, and contributes to the replication crisis in the applied sciences. I will develop a novel statistical theory in which all data-collection and decision-aspects may be unknown in advance, possibly imposed post-hoc, depending on data itself in unknowable ways. Yet this new theory will provide small-sample frequentist error control, risk bounds and confidence sets. I base myself on far-reaching extensions of e-values/processes. These generalize likelihood ratios and replace p-values, capturing 'evidence' in a much cleaner fashion. As lead author of the first paper (2019) that gave e-values a name and demonstrated their enormous potential, I kicked off and then played an essential role in the extremely rapid development of anytime-valid inference, the one aspect of flexibility that is by now well-studied. Still, efficient e-value design principles for many standard problems (e.g. GLMs and other settings with covariates) are still lacking, and I will provide them. I will also develop theory for full decision-task flexibility, about which currently almost nothing is known. A major innovation is the e-posterior, which behaves differently from the Bayesian one: if priors are chosen badly, e-posterior based confidence intervals get wide rather than wrong. Both the existing Wald-Neyman-Pearson and Bayesian statistical theories will arise as special, extreme cases of the new theory, based on perfect (hence unrealistic) knowledge of the data-collection/decision problem or the underlying distribution(s), respectively.

Keywords: e values,anytime valid hypothesis testing,anytime valid confidence sets,foundations of statistics
High throughput phylogeography of tumors: how the tissue environment influences cancer evolution? (Tx-phylogeography)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator 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: Israel
Call: ERC CONSOLIDATOR GRANTS (ERC-2022-COG, 2022)
Start date: 2023-04-01
End date: 2028-03-31
Duration (months): 60.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 1
Project status: SIGNED

The tumor microenvironment (TME) is a dynamic ecosystem wherein tumor cells, immune cells and stromal cells interact and evolve. One of the primary characteristics of cancer progression is the diversification, selection and expansion of tumor sub-clones in manner that largely depends on the TME, e.g., through immune responses or metabolic crosstalk. Advances in single-cell and spatial genomics provide exciting opportunities for studying how tumors evolve in their tissue context, by lending an information-rich perspective on which cell subsets are present and how they might interact. However, fundamental questions, which require the knowledge of how single tumor cells are related sub-clonally, remain challenging to study through that perspective. Fundamentally - what characterizes the immediate cellular environment of successful subclones? Here, we develop transcriptional phylogeography - a paradigm for studying tumor development in-situ, on a transcriptome-wide scale, and at single cell resolution. Our work will leverage studies by us and others that utilized CRISPR/Cas9 mutations coupled with single cell RNA sequencing to infer the lineage structure of thousands of single cells at a time. Adapting this system for in-situ profiling, we will generate the first of its kind phylogeography dataset of a tumor model. This data will allow us to identify tissue locations that harbor critical sub-clonal properties such as unrestrained growth, dedifferentiation, and metastatic seeding, and thereby investigate - through the lens of high throughput genomics- how the TME is associated with these properties. We will also identify and offer solutions for outstanding analytical questions in this nascent area, from lineage inference given sparse data to characterizing the metabolic aspects of tumor-TME cross talk. Together, these studies will help establish new causal links between the TME and tumor evolution and lay the foundation for transcriptional phylogeography analysis.

Keywords: single cell genomics,single cell lineage tracing,tumor evolution,tumor immunology,metabolism,phylogenetics,algorithms
Adaptive Fire Testing: A new foundation stone for fire safety (AFireTest)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Products and Processes Engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Belgium
Call: ERC STARTING GRANTS (ERC-2022-STG, 2022)
Start date: 2023-09-01
End date: 2028-08-31
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: SIGNED

The current fire safety paradigm is based on a set of standardized tests which have been developed as part of a prescriptive design framework, and do not provide in-depth understanding of construction products’ fire performance. The resulting incomplete fire performance characterization hampers the much needed innovation in the built environment. The current fire safety paradigm also places tremendous emphasis on the expertise of controlling bodies (AHJ), making them responsible both for the specification of detailed prescriptive rules, and for the acceptance of performance based designs. This is unsustainable in the face of innovation. AFireTest strives to induce a paradigm shift in fire safety science and engineering (FSSE). The core of AFireTest is the development of Adaptive Fire Testing whereby optimum fire tests are determined from the infinite number of possible test specifications through the maximum expected net information gain (Value of Information, VoI). This will be developed using modern glazing and load bearing glass as innovative case study, resulting in breakthroughs in fire performance understanding. Secondly, a framework for advanced ‘grey’ surrogate modelling will be developed, combining the pattern identification strengths of machine learning with fundamental FSSE constraints. This will introduce a powerful new tool to FSSE and enable the VoI optimization. A grey modelling approach will also be developed for quasi-instantaneous building specific risk evaluations, allowing a new approach to the AHJ acceptance of fire designs. The future operationalization of the new framework for fire design acceptance will require large follow-up investments. Thus, stakeholder buy-in is crucial. Therefore, AFireTest will develop a methodology for the cost-benefit evaluation of fire safety frameworks. For the first time, fire safety approaches will be evaluated from the perspective of Law and Economics, laying the groundwork for an entirely new field of study.

Keywords: fire safety experimental design value of information surrogate model compliance framework
Strategic Energy Technologies Plan Annual 2023 Conference in Barcelona, Spain (SETPlan 2023)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Cluster 5 other
Destination: Other Climate, Energy and Mobility destinations
Action type: Coordination and support actions
Countries involved: Spain
Call: Support for the SET Plan Conference in 2023 (Presidency event) (HORIZON-CL5-2023-SETPLAN-IBA, 2023)
Start date: 2023-04-01
End date: 2024-01-31
Duration (months): 10.0
Total project cost (EUR): 466098.75
EU funding (EUR): 250000.0
Participants: 1
Project status: CLOSED

FECYT, as a foundation in charge of supporting the Ministry of Science of Spain, presents a proposal to host the SET Plan Conference 2023 in Barcelona, Spain, during the Spanish Presidency of the EU. The Conference will take place in Barcelona on 13 - 14 November 2023. The agenda includes 3 high-level panels dedicated to technological sovereignty, energy system resilience and the European Solar Strategy, where we expect the attendance of Commissioners Simson and Gabriel. In addition to this, 4 thematic sessions dedicated to Energy Storage, Energy Efficiency, Offshore technologies, and biofuels will take place, as well as interactive sessions for crosscutting issues. The event will count with the attendance of the Spanish Minister of Science and Innovation, the Minister of Industry, Trade and Tourism, and the Spanish Minister for Ecological Transition. The first day will be closed by a formal dinner. The Conference will promote energy research and innovation across the EU and enable discussions among different public and private stakeholders. The results will include, among others, recommendations for the SET Plan Implementation Working Groups, and for the future of the EU research and innovation programmes.

Keywords: setplan,energy,strategic autonomy,technical sovereignity,energy system resilience
Explaining human decision-making by combining choice and process data (IMMERSION)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Human Mobility, Environment, and Space
Panel description: Human geography, demography, health, susta inability science, territorial planning, spatial analysis
Countries involved: Denmark
Call: ERC STARTING GRANTS (ERC-2024-STG, 2024)
Start date: 2024-10-01
End date: 2029-09-30
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: SIGNED

Decision-making is a core element of human activity, and the decisions we make can have significant consequences for ourselves, others, and the world we live in. Thus, the ability to explain and predict decision-making is vital for improving individual and societal outcomes, especially when addressing global challenges like climate change, sustainable energy, ageing populations, and public health. Mathematical models of decision-making can help us to understand and predict human behaviour. Despite significant progress, several scientific challenges persist in the applicability of advanced behavioural models to real-world problems. Many models focus on predicting decision outcomes rather than explaining the decision process itself. Information contained in neurophysiological process data that emerge during decision-making are often ignored, and methods for collecting behavioural data fail to create realistic impressions of scenarios representing the future. IMMERSION aims to advance the study of human decision-making by developing new innovative methods for combining choice and process data. This includes new models for integrating choice and process data, new statistical inference procedures tailored to such models, and new methods for collecting rich behavioural data in immersive experiments. The proposed research will create a paradigm shift in behavioural research with impacts on many application domains. IMMERSION will equip researchers with a new powerful toolkit for extracting deep behavioural insights from rich data using advanced models. The proposed research includes substantial empirical work applying IMMERSION’s methodological innovations to real-world problems with implications for the human-centric design of future transport systems. This work includes case studies to explain and predict human decision-making in the contexts of transportation infrastructure development, pedestrian-autonomous vehicle interactions and pedestrian wayfinding.

Keywords: choice modelling,decision making,discrete choice analysis,behavioural modelling,extended reality,data collection,human centric transport systems
Human and avian Pattern Recognition Receptor activation of cell death pathways: impact on the host inflammatory response to zoonotic infections. (AviCeD)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Immunity, Infection and I mmunotherapy
Panel description: The immune system , related disorders  and their mechanisms , biology of infectious agents and infection, biological basis of prevention and treatment of infectious diseases , innovative imm unological tools and approaches , including  therapies
Countries involved: United Kingdom
Call: ERC ADVANCED GRANTS (ERC-2024-ADG, 2024)
Start date: 2025-12-01
End date: 2030-11-30
Duration (months): 60.0
Total project cost (EUR): 2498468.0
EU funding (EUR): 2498468.0
Participants: 1
Project status: SIGNED

Zoonotic infections, particularly with viruses or bacteria, continue to be important threats to humans globally. These infections can cause severe inflammatory disease in humans, but may be tolerated by their animal hosts although how this occurs is unclear. Many human diseases have underlying inflammatory aetiologies so determining how diversity in host-pathogen responses occurs across animal species provides unique opportunities not only to identify fundamental inflammatory mechanisms, but also to find new anti-inflammatory therapeutic targets. Previously we found how the zoonotic bacterium Salmonella is sensed by Pattern Recognition Receptors (PRRs) to form macromolecular signalling platforms that trigger interconnected, caspase-dependent cell death pathways critical for inflammation and infection control. How these signalling platforms form is unclear. Our cross-species analysis identified major differences in key constituents of these signalling platforms which, we hypothesise, will alter the host inflammatory response to zoonotic pathogens. Our recent discovery of a novel caspase with defective activity against Salmonella in Carnivora spp supports this idea. AviCeD will leverage our new suite of techniques where we endogenously label, mutate or remove innate immune proteins in cell-lines from any species to determine how PRR-driven cell death platforms form in cells in response to infection. We will compare cells from chicken and ducks infected with Salmonella or Influenza virus, as reservoirs species with differential severity in their host inflammatory responses to these pathogens, performing proteomic analysis alongside evolutionary analysis and functional validation to identify key regulatory proteins. We will then analyse the physiological relevance of differential cell death pathway wiring on cell extrinsic inflammatory consequences in two-cell infection models.

Keywords: pattern recognition receptors,toll like receptor,inflammasome,nod like receptor,inflammation,cell death,pyroptosis,necroptosis
Improved high fidelity Hydrodynamic Model for Floating Offshore Wind Turbine Analysis (FloatingWindExcel)

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: Denmark
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): 230774.4
EU funding (EUR): 230774.4
Participants: 2
Project status: SIGNED

The Floating Offshore Wind Turbine (FOWT) industry has rapidly grown from 2.3MW in 2009 to an impressive 15MW by 2023, with plans for larger 20MW and 25MW capacities. This growth poses challenges in cost, fabrication, manufacturing, and installation due to increased floater size and weight. Low to medium-fidelity hydrodynamic engineering models and higher safety factors are one of the reasons for this surge. High-fidelity models offer the most accurate representation of the underlying physics, minimizing approximations, however, they come with high computational costs. Our primary objective is to adopt high-fidelity CFD-based hydrodynamic models by significantly reducing computational time using the SWENSE and integrating them into aero-elastic solvers for FOWT analysis. This methodology involves decomposing the velocity field into incident and complementary velocity fields and solving only the complementary velocity field in the CFD domain, saving significant computational time. The developed solver will be systematically upgraded (four work packages) from single floating body to multi-body FOWT simulations. The resulting solver will play a pivotal role in unraveling the aero-hydro-structural behavior of FOWT systems during extreme wave interaction, fostering advancements in Operation and Maintenance research, and effectively addressing technical knowledge gaps in the FOWT field. There will be experiments to analyze boat-FOWT interaction as well as to evaluate the developed solver. My host institution runs the renowned Aeroelastic tool HAWC2, and my supervisor is a world-renowned expert in the numerical development of FOWT and physical model testing. He is well-suited to mentor this project with his expertise in both hydrodynamics and aeroelasticity. This endeavor will bridge the gap in my expertise, transforming me from a Hydrodynamicist into an overall floating wind energy specialist, while gaining a knowledge base from aerodynamics and aeroelasticity.

Keywords: wind energy,offshore,floating wind turbines,cfd,openfoam,multibody interaction,multi fidelity,aeroelastic,hawc2,openfast,mooring,fowt,swense,waves
Exploring the interplay between socioeconomic position and mental health through familial and genetic measures (MentalSEP)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting 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: Denmark,Spain
Call: ERC STARTING GRANTS (ERC-2024-STG, 2024)
Start date: 2025-09-01
End date: 2030-08-31
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 2
Project status: SIGNED

There is robust evidence that low socioeconomic position is associated with an elevated risk of subsequent mental disorders, but the validity of these findings is debated. This association could be causal or could be the result of failing to adjust for underlying risk factors that cause both a lower socioeconomic position and a higher risk of mental disorders. Existing studies (i) do not fully account for familial and genetic underlying factors, (ii) do not use measures of socioeconomic position at different levels (e.g., individual and neighborhood), and/or (iii) do not consider mental health beyond clinically diagnosed mental disorders. MentalSEP addresses these fundamental gaps by developing a novel approach to estimate the association between childhood socioeconomic position and subsequent mental health in a comprehensive way using Danish population-based data (~11 million persons). I plan to consider both genetic and familial susceptibility and different aspects of socioeconomic position and mental health. Additionally, I propose two important methodological developments to overcome the limitations of current techniques: (i) to adapt new measures of familial susceptibility through the health and socioeconomic history of family members, and (ii) to develop data-driven methods capable of combining data sources from non-overlapping sample populations. The broad guiding hypothesis of this project is that innovative methods bridging different disciplines will reveal more meaningful information on the potential effect of socioeconomic position on mental health. MentalSEP is ground-breaking both in relation to the methods it will develop and their application. The project will deliver cutting-edge knowledge about social inequalities in mental health, helping us better guide policies aimed at reducing their impact. In addition, the project will explore pioneering methodological approaches that have the potential to be a major advancement in the field of epidemiology.

Keywords: register based epidemiology observational studies psychiatric epidemiology social inequalities data linkage family risk scores