Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : QS-Gauge (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Université d'Innsbruck — Pays : Autriche — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 750626.0 €

Gauge theories are ubiquitous in physics with applications ranging from fundamental high-energy physics(HEP) over emergent condensed matter phenomena to quantum information science and technology. Their study often requires non-perturbative numerical simulations and several regimes of interest remain inaccessible due to the numerical sign problem of Monte-Carlo simulations. Motivated by recent advances in the control of synthetic quantum systems QS-Gauge addresses the quantum simulation of lattice gauge theories (LGTs) beyond the reach of classical computations. Our objectives are (i) to establish a class of regularized gauge theories co-designed for quantum simulation, enabling (ii) the construction of digital quantum algorithms tailored to “LGT-aware” hardware, and (iii) to analyze paradigmatic phenomena such as confinement using classical tensor network (TN) simulations which serve as benchmarks for quantum devices. QS-Gauge is based on an unconventional generalization of the well-established Kogut-Susskind Hamiltonian formulation of LGTs, where the defining non-abelian Lie algebra is deformed to a quantum group. The resulting theories are related to string-net models employed for the classification of topological order in condensed matter which we will leverage to adapt TNs to HEP applications. As these truncated non-abelian LGTs are efficiently represented as multi-level systems, we pursue the development of quantum algorithms for qudits instead of qubits as elementary information carriers. In close collaboration with experimental colleagues and in synergy with the development of early fault-tolerant hardware, we focus on trapped-ion qudit quantum computers and fermionic alkaline-earth Rydberg atoms for optimized (fermion-)qudit architectures. Our results are expected to have far-reaching interdisciplinary impact and inform the development of future quantum devices, also for condensed matter physics, quantum chemistry and general quantum information processing.

Mots-clés : quantum simulation,trapped ions,rydberg atoms,tensor network methods
Projet ERC : INN-TIME (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Centre National de Recherches Oncologiques — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CNIO
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

Circadian rhythms (CRs) are the biological response to the periodic rotations of the Earth, and allow fundamental adaptations of organisms to a changing environment. CRs are molecularly controlled in every cell by a set of transcriptional factors that control, and are influenced by, core biological processes including metabolic, immune, and proliferative. My previous studies established, for the first time, that innate immune cells regulate the circadian physiology of tissues, including the susceptibility of the lung to be metastasized. In INN-TIME, I ask the reciprocal question to reveal if tumors take advantage of, and subvert, CRs of the innate (immune and stroma) compartments to escape anti-tumoral defense. INN-TIME Aims to understand how oncogenic processes rewire CRs of the host and to elucidate strategies that halt this subversion as a new approach to fight cancer. Using lung cancer as proof-of-principle, I will first investigate cell-intrinsic circadian programs in tumors (Aim1). Next, I will define how tumors co-opt circadian clocks of the host and explore how the molecular clock of innate immune (Aim2) and supporting stromal cells (Aim3) impacts tumor growth, both molecularly and functionally. By integrating multiple transcriptomics and functional approaches, INN-TIME will discover novel regulatory programs in tumors using a circadian approach, and pave the way to design strategies to prevent cancer by interfering with tumor-supportive circadian programs. INN-TIME will revolutionize the way we understand cancer, as it will identify the malignant roots of circadian rhythms and their impact on host defense. This research will establish a new paradigm by revealing the mechanisms underlying pro-tumorigenic clocks, and will provide robust foundations for new therapies in a set of disorders in which circadian clock (dys)functions are implicated.

Mots-clés : circadian rhythms,innate immunity,lung cancer
Projet ERC : TopBMemory (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and I mmunotherapy
Entité participante : Hôpital universitaire de la Charité de Berlin — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : Charité
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499963.0 €

The novel COVID-19 vaccines have effectively reduced morbidity and mortality but unexpectedly failed to provide long-lasting sterilizing immunity. While specific serum antibody (Ab) titers were durable, local upper respiratory tract (URT) mucosal Ab responses were surprisingly short-lived. This shows both our lack of and need for a deeper understanding of URT mucosal immunity and its distinctions from systemic immunity. My proposal is designed to answer two key questions arising from this: How does the initial exposure site—mucosal or systemic—shape and imprint immune memory? And how is this imprinting reprogrammed by subsequent exposures via different exposure routes? In the TopBMemory project, I will: (1) delineate how the antigen (ag) nature and primary exposure site shape human memory B cell (MBC) subset heterogeneity and their imprinting. I will generate the first single-cell (sc) multiomic profiles of ag-specific (ag+) MBCs with context-specific imprints by a project-specific pipeline integrating transcriptomic, epigenomic, and phenotypic data. (2) Determine how alternative re-exposure sites reprogram existing imprints—overwrite or complement them—which will be the first demonstration of the potential for natural imprint reprogramming in MBC. (3) Test targeted reprogramming of MBC subsets within tonsil and nasal mucosa-derived organoid co-culture systems. My findings will significantly advance understanding of MBC ontogeny and plasticity, both in host protection and also immunopathologies, and inform the development of a new generation of vaccines and therapies. The groundbreaking nature of TopBMemory lies in its first large-scale contextualization of human ag+ MBC subset origins and functions, exploring their responses and adaptions to varying routes of ag re-exposure. This is complemented by the development of innovative toolkits for sc multiomics and MBC (re-)programming within advanced organoid systems, to explore and guide precise manipulation strategies.

Mots-clés : immunological memory,human,memory b cell,upper respiratory tract urt,infection,vaccination,mucosal immunity,systemic immunity,epigenetics,imprinting,reprogramming,varicella zoster virus vzv,respiratory syncytial virus rsv,antigen specific,organoids,tonsil,nasal mucosa,tetanus toxoid tt,memory b cell ontogeny,flow cytometry,single cell,multiomics,atac seq,rna seq
Projet ERC : MAD-TENSOR (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Materials Center Leoben (Austria) — Pays : Autriche — Rôle : PI
Acronyme de l'entité : MCL
Type d'entité : Recherche
Financement ERC de l'entité : 1498705.0 €

Metallic alloys form the backbone of modern infrastructure and technology in our society. Hence, alloys must be understood, not only by their macroscopic behavior, but rather through consideration of the interactions between many length scales, from angstroms to meters. In general, understanding cannot be developed by experiments alone, beyond observations of snapshots, but must be combined with atomistic simulations that can provide a deeper understanding of the nanoscale mechanisms that govern the dynamics observed in experiments.  Machine-learning potentials (MLIPs) have been a breakthrough for providing the quantitative accuracy of quantum mechanics to atomistic simulations, required to predict the correct mechanisms. However, developing a universal MLIP that is quantitative over the whole composition space has thus far not been achieved. Current available approaches lack either computational efficiency or accuracy. Another breakthrough is required.  To address these challenges, I propose to develop a novel architecture for potentials, equivariant tensor networks (ETNs), based on low-rank representations of high-dimensional tensors to reduce the number of parameters in approximating multidimensional functions. The two distinguishing features of ETNs that are key for developing predictive universal potentials are  (i) high-dimensional convolutions represented using low-rank tensor networks,  (ii) their factorization into small, equally-sized, but highly repetitive, operations which are lucrative for massive parallelization on modern HPC architectures, such as GPUs. Moreover, ETNs will allow to solve two additional urgent problems:  (a) efficiently adding magnetic degrees freedom to the MLIP's functional form to compute magnetic properties with atomistic simulations,  (b) the creation of an "averaged" ETN potential that allows to compute material properties of random alloys without requiring sampling over thousands of simulations of the true random alloy.

Mots-clés : atomistic simulations machine learning potentials tensor networks crystalline defects magnetic alloys random alloys
Projet ERC : Immuno-SBC (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Antoni van Leeuwenhoekziekenhuis — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : AVL
Type d'entité : Recherche
Financement ERC de l'entité : 1336500.0 €

Approximately 1 in 5 newly diagnosed cancers is a second or subsequent cancer related to treatment for a first cancer. Second breast cancers (SBCs) are the most commonly diagnosed. Those who develop SBCs have reduced treatment options and worse outcomes than comparable individuals with first primary breast cancers. There are over 12 million female cancer survivors in the EU, of whom at least 15% will develop an SBC. A better understanding of the etiology and risk factors for SBC is therefore essential. There is an intriguing and poorly understood negative association between systemic autoimmune diseases and breast cancer, repeatedly documented in distinct populations. My preliminary data further suggests that systemic autoimmune disease interacts with chemotherapy receipt to modify the risk of SBCs. However, no research groups have interrogated the interaction among autoimmunity, cancer treatment, and SBC risk. I propose to address this gap by bringing together population-based studies, multi-omic tools, and innovative statistical modelling. I have proposed three complementary Scientific Aims to understand the epidemiological and biological relevance of autoimmune disease in SBC. In Aim 1, I will use a novel approach to link large cohorts of cancer survivors with medical data to capture the course of autoimmune disease after cancer and its relationship with SBC risk. In Aim 2, I will use germline genotyping data to define "autoimmune states" reflecting the true range of sub-clinical autoimmune phenotypes. In Aim 3, I will test the association between autoimmune state and SBC risk, and the interaction with chemotherapy. This project thus introduces a novel paradigm for understanding of the etiology of treatment-associated cancers. Given the fundamental importance of immune state in cancer outcomes, and the number of people at risk of SBC, this project will have a profound impact on cancer survivorship research.

Mots-clés : breast cancer autoimmunity chemotherapy radiotherapy genetics statistical modelling late effects cancer survivorship
Projet ERC : SPECTRA (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université d'Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499886.0 €

What is the cost of a task if we have to perform it many times? This fundamental question appears throughout computer science (direct-sum problems), mathematics, and physics. Challenging, protagonistic problems of this kind, that play a central role in this proposal, are fast matrix multiplication in algebraic complexity theory, Shannon capacity in graph theory, efficient asymptotic entanglement transformations in quantum information, and the cap set problem in additive combinatorics. Despite tremendous effort, structured approaches avoiding known barriers have been lacking.  Recent work by the PI has built the theory of asymptotic spectrum duality, which Strassen originally introduced to study matrix multiplication, into a powerful theory for direct-sum problems in various areas—from algebraic complexity, to discrete mathematics, quantum information and computational complexity—characterizing such problems in terms of an “asymptotic spectrum”. This approach opens a wealth of unexplored routes towards solving direct-sum problems via methods from algebra, analysis, combinatorics, and optimization.  This proposal develops the asymptotic spectrum approach and synergetic applications to direct-sum problems: their general structure theory, methods for specific problems (matrix multiplication, Shannon capacity, and beyond), and interactions among them. Key objectives are: (1) to construct, through topological properties of asymptotic spectra, entirely new kinds of fast matrix multiplication algorithms and circumvent barriers of existing methods; (2) determine the Shannon capacity and its properties through a new approximation approach induced by asymptotic spectrum distance and structured (orbit) packings; (3) determine the structure (topological, geometric, computational) of asymptotic properties of quantum entanglement (tensors); and (4) develop the structural theory and broad applications of asymptotic spectra and interdisciplinary methods for direct-sum problems.

Mots-clés : algebraic complexity theory,matrix multiplication,shannon capacity of graphs,asymptotic rank conjecture,slice rank method,direct sum problems
Projet ERC : Epaphus (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : Université d'Amsterdam — Pays : Pays-Bas — Rôle : Partner
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 514060.4 €

A fundamental goal of astronomy in the coming decades is to determine whether a planet around another star could be habitable. An important piece in this habitability puzzle is the environmental conditions of an exoplanet: the 'space weather' it experiences. However, determining the space weather conditions around a star has been challenging because of the limited sensitivity of low-frequency radio telescopes. A low-frequency radio detection of a star or exoplanet can provide evidence of plasma ejection from the star, or a direct measurement of an exoplanet's magnetic field strength. Such information determines if a planet's atmosphere can survive the onslaught of stellar activity. Recently, I achieved the first low-frequency detections of quiescent stars via a novel polarisation technique using the telescope LOFAR. The radio emission is likely generated by star-planet interactions -- representing a new way to discover exoplanets and characterise their space weather environment. These first detections represent the tip of the iceberg in terms of other detectable stellar systems as I expand my observations over the northern sky. I am on the precipice of conducting the first ever population analysis of the types of stars that emit at low frequencies, revealing whether they are orbited by exoplanets, and what environmental conditions such planets experience.  This grant will allow me to scale my new low-frequency calibration and polarimetric techniques to determine the space weather of stars and exoplanets via: 1) determining the radio periodicity from star-exoplanet interactions; 2) directly detecting radio emission from an exoplanet; and 3) tracing the kinematics of ejected stellar plasma.  Such information will facilitate a leap in our understanding of the plasma environments around stars and the underlying laws governing the generation of planetary magnetic fields -- information that will guide us in the coming revolution in exoplanet habitability.

Mots-clés : space weather,space physics,radio stars
Projet ERC : GUT-FEEL (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Leibniz-Gemeinschaft — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : WLG
Type d'entité : Recherche
Financement ERC de l'entité : 1499980.0 €

A “gut feeling” is an intuition arising without conscious reasoning. This idiom reflects a profound biological truth: the gut is directly connected to subcortical systems that regulate arousal, mood, and behavior. However, brain-body theories often overlook these connections and their influence on arousal, a key mechanism through which the gut affects cognition. Moreover, we lack a detailed understanding of how different time scales of gut activity -from rapid contractions (seconds to minutes) to slower hormonal fluctuations (minutes to hours)- interact with brain dynamics, mood, and cognition. Critically, this gap also extends to mental health, where gut signals are increasingly recognized for their crucial role, yet a comprehensive mechanistic framework linking specific symptoms to altered brain-gut interactions remains absent.  GUT-FEEL will address these challenges by systematically investigating gut-brain interactions across the vigilance, affective, and physiological dimensions of arousal, using pharmacological manipulations of the gut and brain. By combining non-invasive measurements of stomach activity with a dense, hourly sampling of gut hormones, I will probe how fast and slow gut signals interact with brain activity, captured simultaneously through electroencephalography and functional magnetic resonance imaging. This novel approach will allow me to untangle the complex web of interactions between the gut and the brain, both in healthy individuals and in those with depression.  By positioning the gut as a critical modulator of brain function, GUT-FEEL will reshape our understanding of the intricate links between the brain, body, and mind. This groundbreaking approach will push the boundaries of cognitive neuroscience and pave the way for gut-focused therapeutic interventions, revolutionizing how we understand and treat mental health conditions such as depression. In doing so, GUT-FEEL is set to redefine the future of brain-body research.

Mots-clés : stomach,gastric,hormones,gut,fmri,eeg,depression,electrogastrogram
Projet ERC : FluMAB (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université d'Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499838.0 €

One of the most life-threatening consequences of global warming is the perturbation of natural ecosystems. Among the detrimental impacts, the increased frequency and intensity of Cyanobacterial blooms (overgrowth of microscopic bacteria in aquatic systems) seriously threaten drinking water and devastate ecosystems and the economy.  The challenge now is to accurately predict the formation of Cyanobacterial bloom and find feasible mitigation strategies. This poses a new paradigm in complex fluids and flows where rheology, fluid mechanics, and biophysics are intertwined across scales: (1) rheological properties on the microorganism level (few microns), (2) mesoscopic phenomena of formation and fragmentation of Cyanobacterial colonies (hundreds of microns), and (3) macroscopic dispersion of colonies under laminar and turbulent flows in the aquatic system (meters). Hence, fundamental knowledge of rheology and fluid mechanics of Cyanobacterial bloom formation is urgently needed.  I will tackle this multiscale problem with a set of highly controlled laboratory experiments and numerical simulations. The novel experimental setups combine rheological methods with advanced mechanical manipulation of cells, tomography, particle tracking, flow visualization, and microscopy. The combination of experiments, statistical modeling, and simulations will result in many first-ever measurements and analyses, unravelling the rheological and mechanical properties of the cells/colonies, and revealing details of aggregation and fragmentation of Cyanobacterial colonies under various hydrodynamic and environmental conditions.  This project lays out an ambitious effort to overcome current limitations and uncover the complex multiscale interactions between rheology, fluid mechanics, cell biophysics, and colony formation and fragmentation. My findings will open new avenues in creating prediction tools and effective solutions to combat Cyanobacterial bloom.

Mots-clés : viscoplastic fluids
Projet ERC : ClimateFiGS (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Université d'Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499899.0 €

The impact of climate change on people’s lives and livelihoods is increasingly hard to ignore, and is moreover characterized by trenchant inequities: wealthy countries generate the vast majority of global CO2 emissions, but poor nations overwhelmingly suffer the consequences. In response, wealthy nations have pledged to mobilize US$100 billion annually in “climate finance” to help their more vulnerable counterparts. The past decade has seen climate finance nearly double, but we know very little about what happens when these resources reach their intended beneficiaries in the Global South. As such, we lack information about where and how climate finance can have the greatest impact, and what constitutes the greatest areas of unmet need. ClimateFiGS develops a new theory to understand the allocation and spending of climate finance within Global South countries. The project considers how leaders’ characteristics, including their gender and age, condition their responses, as well as the relative emphasis they place on mitigation (i.e., risk protection) vs. adaptation (i.e., risk management). This approach recognizes the agency of Global South leaders, and expands the knowledge frontier on substantive representation, distributive politics, and environmental policymaking. ClimateFiGS breaks empirical ground by creating new global data on the mobilization of climate finance, as well as by studying detailed patterns of budget allocation and expenditure in three purposefully selected African countries. The project further adapts methods from social activism to map the power dynamics that drive climate finance decision making within countries, and traces the processes that lead certain sectors and districts to be prioritized. ClimateFiGS is thus poised to generate knowledge to address one of the world’s most “wicked” problems: How can we avert the most devastating impacts of climate change for the world’s most vulnerable?

Mots-clés : climate finance budget transparency substantive representation