Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : EpiCancer (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Institut Weizmann — Pays : Israël — Rôle : PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Epigenetic regulation of gene expression- the mechanism responsible for establishing and maintaining cellular identities during development- is frequently deregulated in cancer. Our working hypothesis is that this deregulation confers upon cells phenotypic plasticity, resulting in intratumor heterogeneity, which is key to tumor development, metastasis, and drug resistance. In EpiCancer, we seek to provide the technological means to address fundamental issues concerning epigenetics in cancer. Namely, we intend to develop, apply, and validate single-cell and single-molecule epigenetic analysis methods that can parse the function of this network and its heterogeneity in human cancer, and utilize it for cancer diagnosis. We will build a rich arsenal of tools to profile the combinatorial epigenetic network in primary tumors and blood taken from cancer patients at multiple scales of resolution (Aims 1 + 2). We will apply these systems to elucidate the function and connectivity between epigenetic modifications in breast cancer and lymphoma, and link epigenetic heterogeneity to tumor biology and clinical outcome (Aim 3). We will also establish revolutionary systems for cancer diagnostics and monitoring, leveraging the unique advantages of our single-molecule tools for multi-modal analysis of epigenetic, protein biomarkers, and microRNAs, originating from both the tumor and its microenvironment, in patients’ blood (Aims 1 + 3). The epigenetic technologies we intend to provide the scientific community are set to profoundly impact our understanding of the epigenetic determinants of cancer, as well as our ability to detect cancer at early stage from a routine blood test and identify early disease recurrence. The analysis of a large cohort of tumor and blood samples from the same patients will generate novel datasets that are expected to reveal cancer-specific and patient-specific epigenetic modules and shed light on the contribution of epigenetic plasticity to tumor biology.

Mots-clés : epigenetic technologies,single molecule,single cell,cancer epigenetics,cancer heterogeneity
Projet ERC : JAM2PRINT (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : École polytechnique de Silésie — Pays : Pologne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 207500.0 €

Many of nature’s materials have exceptional properties because their structural organization resulted from the on-demand processing of compartmentalized materials. I want to translate this principle to extrusion-based 3D printing (EBP). EBP is a booming fabrication approach in tissue engineering, as it provides control over material deposition in the submillimetre range in a cost-effective manner. However, due to the many requirements for printable (bio)materials (called inks), only a limited number of chemistries can be effectively used, and typically homogeneous network compositions are obtained even though biomedical and other applications require highly controlled inhomogeneities. Approaches providing high control over local material structure and composition are lacking.  To provide a solution, I will develop a new class of microgel-based materials that jam due to the on-demand induced microgel swelling and undergo secondary crosslinking, both in the flow, resulting in a one-step printing of stable heterogeneous scaffolds with locally varying properties and compositions, relevant for mimicking real tissues. Importantly, the approach eliminates jamming steps before printing, yields unprecedented control over local material composition and structure in the flow, down to the sub-micrometre range, and does not require post-printing crosslinking steps to stabilize the printed structures.  Inspired by nature’s compartmentalized materials and supported by preliminary measurements, my microgels will serve not just as pre-defined building blocks but also as material reservoirs during printing. The approach will be generalizable to different material systems and chemistries and, as such, holds great promise for a new generation of hydrogels and advanced inks with structural and functional properties precisely controlled during and via the printing process. This will impact fields from tissue engineering to soft robotics, agriculture, food and cosmetics.

Mots-clés : bioprinting,extrusion,microgels,jamming,scaffolds,stiffness,structural heterogeneity,shear,tumour
Projet ERC : BioGeoMicrobes (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Institut Weizmann — Pays : Israël — Rôle : PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499999.0 €

Many biogeochemical processes, such as carbon cycling in marine ecosystems, are driven by interactions between micro-algae and bacteria. Global warming changes our oceans, impacts algal-bacterial interactions, and affects the processes these interactions propel. If we are to find ways to ameliorate the effects of global warming, we need to understand the molecular mechanisms that mediate these key algal-bacterial interactions, and integrate this knowledge into a biogeochemical context. A major challenge in studying these interactions – often mediated by secreted metabolites – is their complexity in nature. Therefore, we established ecologically relevant model systems with tunable complexities including algal-bacterial co-cultures, genetically tractable synthetic communities, and mini-cosms to study such interactions in context. These allow us to monitor and manipulate algae, bacteria, and their environment. We will combine microbiology and Earth sciences approaches to generate a “blueprint” of metabolic circuits that shape the algal-bacterial-environmental interaction landscape. Specifically, we will study:  1) The organic and inorganic secreted metabolome of algae and bacteria. 2) The physiological response of algae and bacteria to specific organic and inorganic metabolites, and the metabolic circuitry connecting algae, bacteria, and the marine environment. 3) The influence of climate change on algal-bacterial-environmental interactions, gaining insight into how key players in the ocean will likely respond to future climate. Unveiling mechanisms of microbial interactions under various environmental conditions allows us to understand how future climate will impact these interactions and the processes they drive. Our interdisciplinary research offers a novel framework for studying the role of microbial interactions in biogeochemical cycling, it will contribute to improved climate change models, and will provide valuable data for ocean stewardship policy makers.

Mots-clés : microbial interactions,microbial biogeochemistry,algal bacterial interactions,coccolithophores,emiliania huxleyi,roseobacters,climate change,proxy
Projet ERC : SocialBugs (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Institut Weizmann — Pays : Israël — Rôle : PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499084.0 €

Bacteria are social organisms that interact and coordinate their behaviors to shape our world. Whereas their clonal populations are genetically identical, they contain phenotypically distinct members. This diversity provides resilience to unpredictable environmental changes, such as antibiotic exposure or nutrient depletion. It also facilitates cooperative interactions between different sub-population via specialization in costly activities such as virulence factor production, forming an extended basis for sociality. Yet, the phenotypic landscape in any given species remains largely unexplored due to the technical challenges of profiling individual bacteria, particularly in spatially structured biofilms and host tissues. Recent breakthroughs in microbial single-cell transcriptomics, developed by the PI of the current proposal (Dar et al., Science 2021), now provide a unique opportunity to illuminate this hidden complexity.  This proposal seeks a systematic and experimentally derived view of phenotypic variation. We will comparatively study pathogenic and non-pathogenic Pseudomonas species in three settings, each illuminating distinct core principles of cell-cell variability. In Objective 1, we will focus on free-living populations, building on the massive multiplexing capacity of our method to comprehensively map phenotypic cell states, outline their interplay with physiological and environmental factors, and study their evolution. We will characterize the spatiotemporal dynamics of cell states directly within 3D biofilms in Objective 2, and contextualize our results in vivo during infection in Objective 3, simultaneously measuring host-and-microbe spatial expression.  Comprehensively studying phenotypic heterogeneity is a critical next step for understanding how microbes survive in complex environments, socially interact, and subvert their hosts during infection. If successfully executed, this proposal will shed light on the plasticity that defines microbial li

Mots-clés : phenotypic variation,single cell transcriptomics,spatial transcriptomics,biofilms,pseudomonas,infection
Projet ERC : PLAnT (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Human Mobility, Environment, and Space
Entité participante : Fciencias.id - associacao para a investigacao e desenvolvimento de ciencias — Pays : Portugal — Rôle : Partner
Acronyme de l'entité : FC.ID
Type d'entité : Recherche
Financement ERC de l'entité : 1047267.54 €

Planning of marine areas is being developed worldwide to support ocean sustainability. However, few existing marine spatial planning (MSP) initiatives consider climate change explicitly. This is a critical oversight in a rapidly changing world. At the same time, no formal MSP initiatives are envisioned for Antarctica; it is the only ocean basin globally without MSP under development. Antarctica is changing rapidly with potential repercussions around the planet, particularly for sea-level rise, climate regulation, and marine ecosystems functioning. Developing integrated, sustainable MSP for Antarctica is now more fundamental than ever. Excluding climate effects from MSP will lead to plans that are maladaptive and inefficient in sustaining marine ecosystems and their use under change. By contrast, if designed with climate objectives, MSP can provide substantial benefits while requiring few trade-offs. Efforts must be thus put together to effectively move towards climate-smart MSP in Antarctica and globally. Yet, contextual idiosyncrasies (political, social, economic) limit the effectiveness of such efforts. Understanding what challenges hinder the development of climate-smart MSP, in Antarctica and globally, and pointing ways to overcome such challenges is key. PLAnT will take up, for the very first time, such critical task. It will assess social-ecological vulnerabilities; build future scenarios; support area-based climate action and dynamic solutions; conduct governance analyses; and foster a paradigm shift on how to plan for sustainability and equity under change. Research on complex social-ecological systems rarely leads to one-size solutions, and there is a risk that solutions identified in PLAnT are context specific. Still, PLAnT will inspire nations worldwide to finding pathways and solutions to support ocean sustainability. At a time when the latter is firmly established in the international agenda, taking a leap forward on this topic is ground-breaking.

Mots-clés : marine spatial planning climate change antartica southern ocean sustainable ocean use marine conservation ocean policy ocean governance stakeholder perceptions social ecological systems dynamic management
Projet ERC : PROXIE (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université de Saragosse — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1494667.0 €

Extended Reality (XR) technologies—including Virtual Reality (VR), Mixed Reality (MR), and Augmented Reality (AR)—are rapidly evolving, offering immersive experiences that blend the physical and virtual worlds. While progress has been made in understanding basic perceptual and behavioral processes to create high-quality, engaging content, current perceptual models often oversimplify how users experience these environments. To create truly immersive and effective XR experiences, we need a deeper understanding of how users perceive complex, highly realistic immersive scenarios. Whether to optimize visual fidelity, manage attention, or improve system performance, human perception plays a central role in the XR experience.  PROXIE aims to address this by studying perception in XR environments that mirror the complexity of real-world XR applications, pursuing ecological validity. Rather than focusing on simplified, constrained scenarios as in existing research, we will explore how perception is shaped by both the environment and the tasks users perform. By understanding how users process multisensory inputs while actively engaging in realistic, interactive tasks such as search or free exploration, we can inform content generation, visualization algorithms, and even hardware design to improve XR experiences.  Our goal is to develop computational models of perception that predict how users perceive and respond to immersive environments—whether fully virtual or augmented—based on sensory inputs and tasks. These models will anticipate how users process their surroundings, allowing XR systems to adapt in real time. For example, the models may help optimize visual rendering, sensory feedback, and the overall user experience to match user needs. This will enhance applications such as telepresence, training, and simulations, ensuring XR experiences feel natural and responsive, bridging the gap between laboratory experiments and real-world use.

Mots-clés : extended reality,computational models of perception
Projet ERC : DRESSED-pCCD (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université Nicolas-Copernic — Pays : Pologne — Rôle : PI
Acronyme de l'entité : UMK
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1218088.0 €

Modern quantum chemistry reached a remarkable level of description of atoms and molecules and their interactions. Theoretical approaches are particularly helpful when experimental studies are hampered or slowed down due to a trial-and-error approach. In such cases, computational chemistry can provide the much sought-after understanding of molecular properties and reactivity. Unfortunately, conventional wave function models are too expensive for large-scale modeling or require user control on an expert level, while density functional theory may predict unreliable properties. To break the current paradigm of computational chemistry, novel and neat approximations are desirable. One such innovative approach models many-electron systems using electron pair states. Current electron-pair methods are, however, insufficient to reach chemical or spectroscopic accuracy for large molecules of organic electronics and must be extended to (i) accurately describe electron correlations beyond the simple electron-pairing effects, especially in cases where conventional corrections break, (ii) reliably predict molecular properties of both ground and electronically excited states of closed- and open-shell compounds, and (iii) provide an intuitive and black-box platform for non-expert users. These goals will be achieved by (a) dressing electron-pair states with information extracted from multi-reference wave functions using a bottom-up approach, where each step systematically improves the accuracy of the previous model along the ladder of approximation, (b) designing a black-box interface to automatized quantum chemistry calculations using concepts of quantum information theory, and (c) elucidating the structure-properties relationship using the picture of interacting orbitals. The synergy between an inexpensive but reliable quantitative description and the qualitative interpretation of molecular interactions will accelerate the discovery of new materials in organic electronics.

Mots-clés : coupled cluster,pair coupled cluster doubles,electron correlation,strong correlation,relativistic effects,electronically excited states,spin orbit coupling
Projet ERC : FoundLatt (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Université d'Édimbourg — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1491488.0 €

Despite describing fundamental physics with spectacular accuracy, the Standard Model of particle physics is known to be incomplete. As experimental programmes probe its boundaries at higher energies and with better precision, it is critical that measurements are faced with fully controlled theory predictions. Lattice simulations of Quantum Chromodynamics (QCD) form a major pillar of this effort. However, even with increasing computing capacity, many lattice QCD calculations will not be possible without new techniques.  FoundLatt aims to solve this challenge by developing the first machine learning (ML) foundation model for lattice QCD. As exemplified by the highly successful ChatGPT, these large, general-purpose models have recently shown great promise in other contexts. Combining methods from these contexts with specialised ML methods that already accelerate specific lattice QCD tasks, I will create a lattice QCD foundation model that performs multiple challenging tasks over a range of physical parameters. The main innovation of this programme is a "train once, use forever" methodology, which will involve a centralised investment of effort that supersedes impractical training of non-reusable models.  This objective will be achieved via three complementary work packages (WPs). My team and I will develop and train a foundation model capable of two critical tasks, importance sampling and precise estimation of observables, first for a reduced model of QCD (WP1) and then the full theory of QCD (WP2). We will also develop a method to learn a "quantum perfect" action for QCD, then fine-tune the foundation model to accomplish this (WP3). Such an action has zero lattice discretisation artefacts, thereby removing one of the largest sources of systematic uncertainty. The main output of FoundLatt will be an ML model that is shared openly with the lattice QCD community, unlocking state-of-the-art theory predictions for the next generation of new physics searches.

Mots-clés : machine learning,generative models,lattice qcd
Projet ERC : ENRICH (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Université de Patras — Pays : Grèce — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1965063.0 €

As the world undergoes an unprecedented transformation towards de-carbonized energy generation and electrification of the transportation sector, there is an increasing need for efficient, compact and lightweight power electronics. However, miniaturization of contemporary energy conversion systems is hindered by the performance limitations of the power devices and the size and weight restrictions of the passive components. The ENRICH project proposes a fundamental reconsideration of the entire electric power conversion chain, by co-design novel multilevel converter topologies with new semiconductor structures, based on wide band gap materials, mainly Gallium Nitride (GaN). The envisioned system is inspired from the high-power equivalent of a digital-to-analogue converter, directly controlled by a single reference signal (pseudo-analogue control). This is the first attempt to demonstrate the concept of a solid-state selector switch, which is free from magnetic components and allows all switching elements to be connected in parallel with a common source reference, avoiding the burden of multiple voltage-isolation zones. This radical approach paves the way for true monolithic integration of the entire multilevel inverter on a single chip, in the form of a power processor. The proposed parallel architecture addresses all current integration challenges, such as the crosstalk and back-gating effects, and overcomes the limitations regarding the maximum number of levels. The GaN power processor has huge potential to reach record power densities that are beyond what is currently possible. The ambitious research spans across the fields of Power Electronics, Material Science and Control Theory, and aims to bring numerous benefits with important technological and socioeconomic impact in the automotive, aerospace and renewable energy generation sectors.

Mots-clés : power electronics,wide band gap semiconductor devices,monolithic integration,multilevel converters,power density,miniaturization,energy conversion system,converter control