Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
The Financial Gender Gap (Gender in finance)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance , management
Countries involved: Denmark
Call: ERC STARTING GRANTS (ERC-2024-STG, 2024)
Start date: 2025-08-01
End date: 2030-07-31
Duration (months): 60.0
Total project cost (EUR): 1499130.0
EU funding (EUR): 1499130.0
Participants: 1
Project status: SIGNED

The financial gender gap, i.e., the well-established gender differences in financial decisions, has been the subject of much recent discussion and debate. We know little about what drives this gap though. Because the financial decisions of individuals play an extensive role in determining welfare in all stages of life, the identification of the contributing factors is of crucial importance. This is the pioneering goal of Gender-in-Finance. The overall concept and central contributions of Gender-in-Finance are the following: (1) the project innovates by creating a unique panel data set, comprised of a rich set of experimental measures, including beliefs, expectations, preferences, and the decision-making abilities of individuals, merged with a panel of detailed high-frequency transaction-level bank data, capturing both real-world financial decisions and constraints of individuals. No comparable data set exists and it enables the identification of the factors that contribute the most to the financial gender gap in reality; (2) using this data set, the project offers ground-breaking, evidence-based understanding of the gender differences in financial-choices along several dimensions that contribute to financial well-being; (3) by identifying the factors that contribute to the gender gap in financial choices the project informs the development of models of financial decision making. Ultimately, this research agenda will shed light on what drives gender differences in financial decision making as well as which policies may be effective in narrowing these gaps. Specifically, the novel insights I aim to provide is expected to lead to substantial improvements in the methods used to fight the financial gender gap as the better understanding of the forces behind the financial gender gap will inform the current debate on this issue and provide important lessons to policy makers who have gender equality on their agenda.

Keywords: household finance,behavioral finance,gender finance,transaction level bank data,big finance data,individual financial decision making,experience effect,gender identity,experience effects
Verifiably Safe and Correct Deep Neural Networks (VeriDeL)

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: Israel
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2023-11-01
End date: 2028-10-31
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: SIGNED

Deep machine learning is revolutionizing computer science. Instead of manually creating complex software, engineers now use automatically generated deep neural networks (DNNs) in critical financial, medical and transportation systems, obtaining previously unimaginable results. Despite their remarkable achievements, DNNs remain opaque. We do not understand their decision making and cannot prove their correctness - thus risking potentially devastating outcomes. For example, it has been shown that DNNs that navigate autonomous aircraft with the goal of avoiding collisions could produce incorrect turning advisories. Thus, the lack of formal guarantees regarding DNN behavior is preventing their safe deployment in critical systems, and could jeopardize human lives. Consequently, there is a crucial need to ensure that DNNs operate correctly. Recent and exciting developments in formal verification allow us to automatically reason about DNNs. However, this is a nascent technology, which currently only scales to medium-sized DNNs - whereas real-world systems are much larger. Additionally, it is unclear how to apply this technology in practice. I propose to bridge this crucial gap through the development of novel, scalable and groundbreaking techniques for verifying the correctness of large DNNs, and by applying them to real systems of interest. I will do this by (1) developing search-space pruning techniques, which will enable us to verify larger DNNs; (2) creating novel abstraction-refinement techniques, which will allow us to scale to even larger DNNs; and (3) identifying new kinds of relevant specifications and key domains where DNNs are used, demonstrating the verification of real-world DNNs. This project will result in a sound and expressive framework for automatically reasoning about DNNs, orders of magnitude larger than is possible today. This framework will ensure the safety and correctness of DNNs deployed in critical systems, greatly benefiting users and society.

Keywords: formal methods,verification,neural networks,abstraction refinement,residual reasoning,invariant generation,decision procedures
Skills Markets: Marriage and Labor (SkiM2Lab)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance , management
Countries involved: France
Call: ERC STARTING GRANTS (ERC-2024-STG, 2024)
Start date: 2025-01-01
End date: 2029-12-31
Duration (months): 60.0
Total project cost (EUR): 1313131.0
EU funding (EUR): 1313131.0
Participants: 1
Project status: SIGNED

The distribution of workers across jobs and across different geographic areas has major implications for growth, social welfare and inequality. It is complex but essential to understand the mechanisms behind the allocation of talents in the economy, that is, how skilled individuals choose their jobs and where they live. However, the existing literature on the distribution of skills faces two major challenges. First, it has largely neglected the role of the marriage market and family constraints, although family formation and partner choice are intimately linked to career and location choices and these choices influence each other. Second, it must go beyond the standard one-dimensional classification of skills based on educational attainment alone. This hierarchy underestimates the inequalities that exist between multidimensional and non-hierarchical skill sets. SkiM2Lab will address this challenge in developing state-of-the-art multidimensional matching models with two specific objectives. In the first objective, I will analyze the interactions between the labor market and the marriage market using equilibrium models of matching where individuals and jobs are associated with multidimensional skill sets and are located in different places. Estimating these structural models on household data will reveal how family and labor markets affect wage disparities and occupational segregation by gender and region. In the second objective, I will leverage big data such as online resumes and online job postings, as well as machine learning and natural language processing technologies, to extract skills at the most granular level, build new relevant combinations of skills and include them in a competitive matching model. This will make it possible to propose a new method to identify rapidly relevant emerging skills and their impact on wages and production.

Keywords: matching models,marriage market,labor market,skills,gender gaps,machine learning tools
Ultra-low Temperature SQUID NMR of Strongly Correlated Electron Systems (ULT-SCES-NMR)

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 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-04-01
End date: 2027-03-31
Duration (months): 24.0
Total project cost (EUR): 217965.12
EU funding (EUR): 217965.12
Participants: 1
Project status: SIGNED

Quantum materials reveal their nature at low temperatures, where thermal fluctuations vanish and the system falls into its lowest energy state. However, this state is far from “static”. Quantum fluctuations, arising from the uncertainty principle and the exclusion rules of quantum mechanics, give rise to unexpected phenomena, such as the mediated pairing of electrons, leading to unconventional superconductivity. Prototypical compounds to study these phenomena are heavy-fermion (HF) superconductors. In these materials superconductivity arises near magnetic quantum critical points -- the points at T = 0 where magnetically ordered phases are suppressed and quantum fluctuations are particularly strong. There exists growing evidence that pairing is mediated by magnetic critical fluctuations. One of the best example is the HF superconductor YbRh2Si2 (Tc < 10 mK) in which strong ferromagnetic (FM) as well as antiferromagnetic (AFM) fluctuations were observed. To understand the nature and role of FM and AFM fluctuations in this compound and generally in strongly correlated electron systems (SCES) and to explain their impact on quantum criticality and superconductivity - e.g. the parity of the Cooper pairs - we propose to build a broadband nuclear magnetic resonance (NMR) spectrometer. NMR is a non-invasive and low-dissipation technique, well suited for probing in the stringent ultra-low temperature conditions under which these phenomena occur. Utilizing a DC SQUID sensor, coupled to the pickup of the NMR spectrometer by a flux transformer, is a way of drastically improving signal-to-noise ratio and enable operation at very low static fields, in contrast to standard NMR techniques. This is essential for studying superconductivity. Understanding the relationship between quantum fluctuations and unconventional superconductivity is crucial for developing new materials with higher superconducting transition temperatures and for potential applications in quantum devices.

Keywords: squid,nmr,unconventional superconductivity,ybrh2si2,ultra low temperatures,sces
Mapping path and fate diversity of molecular mechanisms of infection with smart microscopy (InfPathMapper)

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: Life Sciences
Countries involved: Sweden
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-06-01
End date: 2027-05-31
Duration (months): 24.0
Total project cost (EUR): 236340.0
EU funding (EUR): 236340.0
Participants: 1
Project status: SIGNED

Pathogens like Yersinia pseudotuberculosis must rapidly adapt to environmental cues to progress through infection, manipulating host responses to survive and replicate. Understanding these adaptive host-pathogen interactions is key to developing targeted therapies, combating antibiotic resistance, and preventing chronic infections. However, current methods miss rare, transient infection stages, limiting our understanding of infection pathways. My project aims to address this by developing InfPathMapper, a data-driven super-resolution microscopy (SRM) platform to map infection pathways in living cells at molecular resolution. While advances in fluorescence microscopy provide detailed molecular insights, they often struggle with phototoxicity, limited spatiotemporal resolution, and reliance on fixed samples, missing dynamic information of infection processes. My approach will extend a data-driven microscopy platform by integrating adaptive SRM modalities for live-cell imaging of Y. pseudotuberculosis infection, a pathogen with virulence mechanisms conserved across many bacteria. This system will be able to map pathways of individual infection events at super-resolution level in a live-cell fluorescence-based infection assay supported by machine learning to classify pathogen invasion stages and host cell response patterns. Live-to-fix super-resolution mapping of the molecular architecture of critical infection stages will provide new insights into how Yersinia adapts to niche-specific environments and host-induced stress. By combining cutting-edge microscopy with infection biology, the project will not only set me on an excellent pathway toward achieving research independence, it is also expected to contribute valuable knowledge and tools for the broader research community, fostering innovation in the study of other pathogens and dynamic intracellular processes and the fight against infectious diseases.

Keywords: super resolution microscopy,single molecule localization,radial fluctuations,yersinia,infection cycle,live cell,smart microscopy,adaptive imaging
Uncovering the link between bacterial growth and secondary metabolite dynamics in soil biocrusts (GROWMETA)

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: Life Sciences
Countries involved: Austria
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2026-09-01
End date: 2028-08-31
Duration (months): 24.0
Total project cost (EUR): 230184.72
EU funding (EUR): 230184.72
Participants: 1
Project status: SIGNED

Bacterial secondary metabolites are highly valuable to humanity as antimicrobials. However, the antimicrobial discovery rate has been lagging behind rapid resistance development. Our lack of knowledge about when and why different taxa produce secondary metabolites is a major source of difficulty in the discovery process. Studies on Actinomycetes in batch culture have shown that secondary metabolites tend to be produced in stationary phase, but evidence suggests that production dynamics are different in other phyla as well as in situ. The goal of this project is to understand how in situ and in vitro SM production dynamics relate to growth rate and transcriptomic changes in soil bacteria. To achieve this, I will conduct a time-series rewetting experiment on a Negev desert biocrust as a model system of soil with reduced diversity. I will apply quantitative stable isotope probing metagenomics and metatranscriptomics to each timepoint to obtain a specific growth rate and expression profile for each metagenome-assembled genome. I will supplement the in situ data with in vitro expression studies in isolates. Together, this will allow me to assess how growth rate & phase, expression of other pathways, and the soil environment impact secondary metabolite biosynthetic gene cluster expression. The results of this project will give unprecedented insights into the dynamics of secondary metabolite production, challenge long-held assumptions, and ultimately lead to improved discovery pipelines.

Keywords: bacterial secondary metabolites,stable isotope probing,metagenomics,metatranscriptomics,biocrusts
EU Face Advanced Communication for Elders Treasuring in Society (EUFACETS)

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 GRANTS2 (ERC-2022-POC2, 2022)
Start date: 2023-06-01
End date: 2024-12-31
Duration (months): 19.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 2
Project status: CLOSED

EUFACETS aims at maximising the value of the ERC Consolidator Project FACETS by developing a family-oriented social network app based on visage. Some faces were excluded from the forced digitalization of all faces due to the increasing digitalisation of our lives, accelerated by the Covid-19 pandemic: those of the elders. The pandemic was just underlining an already existing issue: face-based social networks have been designed by young people for young people. They focus on connecting people who are distant in space but fail to connect people who are distant in time. They help individuals treasure and share their own memories, those attached to digital pictures and selfies, yet they are oblivious of memories that are enshrined in pre-digital photographs. EUFACETS aims to alleviate this issue by developing an app establishing a new family-oriented social network based on visage. Through the app, members of extended families will be able to digitalize analogic pictures, send it in this digital form to the elder, who will then be able to tell a story about the picture; the story will be made available to the family, which will be able to listen to it and to integrate it with secondary narratives; finally, through facial recognition and artificial intelligence, the app will suggest automatic identification of visages photographed in subsequent pictures and facilitate the reconstruction of the narrative. The solution will grow around the elders, with the only purpose of reconnecting them with their distant relatives, friends, and acquaintances, as well as with the pre-digital past of their visage. This is done without any logics of commodification and control, standardization and commercial exploitation underlying existing face-based digital platforms.
Efficient Confluent Edge Networks (ECO-eNET)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Public-private partnerships
Destination: Smart Networks and Services
Action type: Research and Innovation actions
Partnership: SNS (JU-JTI)
Countries involved: Sweden,Ireland,Switzerland,United Kingdom,Greece,Belgium,Estonia,Germany
Call: Communication Infrastructure Technologies and Devices (HORIZON-JU-SNS-2023, 2023)
Start date: 2024-01-01
End date: 2026-12-31
Duration (months): 36.0
Total project cost (EUR): 3769981.0
EU funding (EUR): 3592544.78
Participants: 12
Project status: SIGNED

The ECO-eNET project will perform foundational research on emerging transmission technologies, to form a new confluent edge network that brings together optical and radio transport to scale to new levels of efficiency and capacity for 6G, by integrating confluent front-/mid-/back-haul (xhaul) with cell-free and distributed multiple-input multiple-output based access networks. The combination of photonic radio fixed wireless and free space optical transmission is used for fixed wireless connections, enabling the creation of an edge mesh network. New monitoring and slice-aware control protocols will unify the radio intelligent controllers with the transport software defined networking to efficiently deliver high-capacity flex grid wavelength multiplexed signals over standard single mode fibre and the fixed wireless links. Radio signals can be flexibly processed at different split phy points throughout the network or remain in analog radio over fibre format end-to-end. The unique ECO-eNET combination of wired and wireless transport is further exploited for wireless control of the wired network segments, enhanced clock synchronization, and optical space and wavelength switching, groomed over FlexE ethernet. AI layer controls are added to orchestrate the federation of edge processing and splitting of AI models for optimum efficiency in executing user applications and smart network control functions. The ECO-eNET project brings together an interdisciplinary team of industry and academic partners to explore the full potential of these important emerging technologies to support the capacity, ultra-high energy efficiency, low latency, and robustness needed in 6G networks.

Keywords: front haul,mid haul,back haul,xhaul networks terahertz fixed wireless transmission free space optical comms sdn nfv control plane open radio networks distributed mimo optical switching
Stochastic Quantisation of Quantum Field Theories with Bosons and Fermions (StoConYuQED)

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: Mathematics
Countries involved: Italy
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-04-01
End date: 2027-03-31
Duration (months): 24.0
Total project cost (EUR): 172750.08
EU funding (EUR): 172750.08
Participants: 1
Project status: SIGNED

The mathematical foundation of Euclidean quantum field theory is a very active research area which has long been a central topic at the intersection of mathematical physics and probability theory. A general probabilistic framework to describe quantum fields called “stochastic quantisation” was proposed in the early 80's by the Nobel prize Giorgio Parisi, in collaboration with Yongshi Wu, and consists in the description of interacting quantum fields via the solution to some stochastic differential equation. The proposal aims at exploring novel directions in stochastic analysis that would allow for a fruitful continuation of the stochastic quantisation programme. Namely, the goal of the proposal is the extension of the known stochastic analytical methods in order to be able to construct quantum field theories for Fermi fields with large-scale singularities and quantum field theories for Fermi and scalar or gauge fields with small-scale singularities.

Keywords: stochastic analysis stochastic quantisation quantum field theory