Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : CHEMTUBIO (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Institute for Bioengineering of Catalonia — Pays : Espagne — Rôle : PI
Acronyme de l'entité : IBEC
Type d'entité : Recherche
Financement ERC de l'entité : 1668750.0 €

Erasers of protein post-translational modifications are ubiquitous regulatory enzymes that control cellular function and are targeted for the treatment of disease. One key example are erasers of histone acetylation, where inhibitors have reached the clinic as cancer chemotherapy. Currently, however, multiple other erasers lack tools of study to determine their relevance and generate clinical candidate molecules. One main reason for this limitation is that erasers display multivalent substrate recognition mechanisms that are difficult to replicate with standard assays in vitro and can jeopardise data translation. I have recently developed a solution to detect histone deacetylase activity in situ not on peptides, as it commonly done, but on semi-synthetic protein substrates and complexes, and still applicable to in vitro screening. My preliminary data supports that this methodology can be applied as a more general strategy, enabling studies and drug development on erasers currently inaccessible. Moreover, it holds great potential to localise eraser activity in living systems and generate maps of enzyme action on endogenous biological structures. CHEMTUBIO aims to generalise in situ eraser activity detection through application to the erasers of tubulin tail detyrosination. These enzymes generate gradients of detyrosination across the cytoskeleton lattice through mechanisms unknown and, even though inhibitors are attractive to treat cardiac and neuronal disorders, no probes are available for further investigation. Here, we will address these knowledge gaps and provide in situ sensors and chemical probes to advance the therapeutic application of detyrosinase inhibition. Furthermore, CHEMTUBIO will develop semi-synthesis methods to allow the study of microtubule lumen modifications. Erasers of luminal acetylation are attractive targets against neuromuscular disease and cancer, and we will provide key mechanistic knowledge to boost future therapeutic developments.

Mots-clés : post translational modification,fluorogenic assay,peptide medicinal chemistry,protein semi synthesis,tubulin
Projet ERC : SCENSUS (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Human Mobility, Environment, and Space
Entité participante : Université Érasme de Rotterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : EUR
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1478000.0 €

How can community enterprises scale their impact and reshape society beyond markets and states? This is an important and timely challenge in realising societal transformations for sustainability, as scholars and policymakers have recently placed high expectations on the transformative potential of communities. While community enterprises are widely known to foster collective action locally, the mechanisms through which they can achieve wider transformations to tackle urgent sustainability challenges such as climate change are poorly understood. SCENSUS aims to identify and understand the mechanisms by which community enterprises can scale their societal impacts. It will analyse initiatives in three key fields (energy, carsharing, repair) in Germany, France, the UK and the Netherlands, to: 1) Develop a unified theory that explains the factors behind the scaling of community enterprises; 2) Analyse the institutional complexity arising as community enterprises scale and the collective mechanisms to manage them; 3) Identify and analyse community enterprises’ strategies to mobilise critical resources and build legitimacy for scaling; 4) Understand the roles of social networks in community enterprises’ scaling dynamics.  This research will 1) advance collective action theory with key insights from social network theory and organisational institutionalism, 2) create a novel approach to scaling, beyond business growth in single organisations and market diffusion, 3) connect different levels of analysis, from community enterprises’ internal functioning to their aggregate development, 4) develop and test an innovative multi-method research design combining large-N statistical analysis, surveys and comparative case studies, to capture dynamic scaling processes. By creating a new interdisciplinary theory of the dynamics of community enterprises within wider social systems, SCENSUS will advance the research frontier on collective action and organisation studies

Mots-clés : community enterprise scaling strategies collective action renewable energy carsharing circular economy
Projet ERC : NEXT-CRC (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Cancer Research Center — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CIC
Type d'entité : Recherche
Financement ERC de l'entité : 1435000.0 €

Colorectal cancer (CRC) ranks among the most prevalent and lethal malignancies globally. However, efforts to translate CRC research findings into clinical advancements have been hampered by inadequate in vitro systems. Even the current gold standard organoid models remain severely limited as they lack the topobiological complexity required to fully capture CRC pathobiology ex vivo. Among other factors, their unsuitability to properly model the multifaceted interactions between CRC and its tumor microenvironment (TME) is particularly limiting, especially since the TME has emerged as an essential element to tumor biology. Crucially, while the TME is being successfully exploited for immunotherapy in many cancers, these therapies remain ineffective in more than 90% of CRC patients. Among the different components of the TME, the colon microbiota is particularly interesting for CRC tumor immunity as in vivo evidence indicates that it can regulate inflammation, modulate immune cell activity, and alter responses to immune checkpoint inhibitors. However, whether anti-tumor immunity can be enhanced through targeted microbiomal-based therapies in CRC patients not responsive to immunotherapy has not been approachable in vitro due to the lack of suitable models. Building upon our expertise in microfluidics, tissue engineering, cell biology, and multiomic technologies, we aim to develop a groundbreaking ex vivo platform capable of integrating complex lymphoid and microbiomal microenvironments in patient-specific tissue-engineered miniature colons. This TME-oriented cancer model will reconstruct functional interactions among diverse components of the TME with unparalleled pathophysiological intricacy. It will be primarily used to shed light on the cancer–microbiota–immune axis, aiming to discover opportunities to harness microbiomal components for improving anti-cancer immunity in CRC. We envision that this project will pave the way towards personalized oncology approaches.

Mots-clés : colorectal cancer,tumoroids,organ on chip,tumor microenvironment
Projet ERC : OutOfSpace (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université de Pavie — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499688.0 €

Is space the main organizer of our mental reality? The answer to this question is apparently "yes". According to recent views, nearly any type of knowledge would be organized through low-dimensional geometries relying on the same computations that are at play in the navigation of the physical space, as attested by the involvement of the hippocampal-entorhinal region in high-level cognition. From an evolutionary standpoint, spatial processing mechanisms might have thus developed from originally mapping the navigable environment to representing cognitive spaces. Moving beyond this spatiocentric view of the human mind, OutOfSpace will test the fascinating yet apparently counterintuitive hypothesis that non-spatial associative learning mechanisms are active (if not the main) ingredients in structuring spatial representations. To pursue this aim, OutOfSpace will employ cognitively plausible computational models (i.e., distributional semantic models) based on non-spatial associative learning mechanisms to extract latent knowledge from natural language; this non-spatial information will be then used to predict a variety of spatial representations, using a pioneering interdisciplinary approach that combines computational, behavioural, eye tracking, fMRI, TMS-EEG and intracranial EEG work in both sighted and blind individuals. OutOfSpace will thus make a breakthrough on two fronts: (i) probing whether language - a non-spatial learning environment - can encode and recode spatial knowledge without the need for a dedicated spatial memory system; (ii) attesting the strict interplay between spatial and non-spatial learning mechanisms in structuring mental representations. More generally, these findings will open the venue to developing a more comprehensive, empirically-based cognitive neuroscience framework for processing and representing spatial information.

Mots-clés : cognitive maps spatial representations associative learning mechanisms semantic memory distributional semantic models hippocampal entorhinal system parietal cortex
Projet ERC : CASPER (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 1497650.0 €

Numerical optimization is a fundamental tool with a growing impact in many disciplines from science to industry. Many of its successes are due to theoretical advances, which are key to developing trust in numerical algorithms. While trust is non-negotiable in many applications, the complexity level of modern and future problems makes it very hard for theory to keep up with efficient proposals. Arguably worse, while both theory and experimental practice are key to the field, their respective recommendations often conflict with each other and the gap between theory and practice gets embarrassingly large.  The main objective of this proposal is to push forward the theoretical foundations of algorithmic optimization to drastically reduce the gap between fundamental theoretical understanding and practical scenarios. To achieve this, we will develop principled and systematic approaches to algorithmic analyses, as well as computer-aided performance certification tools. Whereas my recent works show that such techniques already allow going far beyond the surprisingly few classical templates for algorithmic analysis, they have currently very limited applicability beyond simple scenarios. We will largely broaden the techniques to develop and study modern algorithms with working guarantees that can (i) scale to unprecedented problem and data sizes, (ii) adapt to common problem structures, and (iii) be deployed on modern massively parallel computing environments. On the way, this project will allow for simplified certification and validation of existing theory, an absolute necessity in this era of massive scientific production.  Outcomes of CASPER will include symbolical and numerical algorithmic certification and development tools, as well as algorithms with unprecedented working guarantees. The tools will be released as open-source libraries and algorithms validated on key benchmarks that include challenging machine learning and robotic tasks.

Mots-clés : numerical optimization,complexity analysis
Projet ERC : MOMENTOUS (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 1039009.9 €

We are witnessing a massive shift in the way people consume information. In the past, people had an active role in selecting the news they read. More recently, the information started to appear on people's social media feeds as a byproduct of one's social relations. At present, we see a new shift brought by the emergence of online advertising platforms where third parties can pay ad platforms to show specific information to particular groups of people through paid targeted ads. These targeting technologies are powered by AI-driven algorithms. Using these technologies to promote information, rather than promote products as they have been initially designed for, opens the way for self-interested groups to use user's personal data to manipulate them. European Institutions recognize the risks, and many fear a weaponization of the technology to engineer polarization or manipulate voters. The goal of this project is to study the risks with AI-driven information targeting at three levels: (1) human-level--in which conditions targeted information can influence an individual's beliefs; (2) algorithmic- level--in which conditions AI-driven targeting algorithms can exploit people's vulnerabilities; and (3) platform-level--are targeting technologies leading to biases in the quality of information different groups of people receive and assimilate. Then, we will use this understanding to propose protection mechanisms for platforms, regulators, and users. This proposal's key asset is the novel measurement methodology I propose that will allow for a rigorous and realistic evaluation of risks by enabling randomized controlled trials in social media. The measurement methodology builds on advances in multiple disciplines and takes advantage of our recent breakthrough in designing independent auditing systems for social media advertising. Successful execution will provide a solid foundation for sustainable targeting technologies that ensure healthy information targeting.

Mots-clés : online advertising,micro targeting,cognitive biases,information exposure,online threats and manipulation
Projet ERC : QFT.zip (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : Partner
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 0.0 €

Many-body quantum systems with strong correlations are particularly difficult to understand in the continuum, where non-perturbative techniques are in scarce supply. Direct diagonalization methods are not available, since the Hilbert space is simply too large to be manageable. This inhibits progress in high energy physics, nuclear physics, and in the study of exotic topological phases of matter. On the lattice, tensor network states, a variational class of wavefunctions coming from quantum information theory, have allowed to compress exponentially large Hilbert spaces down to a smaller numerically manageable corner. This has allowed substantial theoretical and numerical advance on the many-body problem on the lattice.  This project will develop continuous tensor network states, a new framework to extend the recent lattice progress to the continuum and quantum field theory (QFT). The originality of the approach is that it will not rely on any discretization of space-time. I will work directly in the continuum, without any cutoff. Low energy states of quantum field theories, which a priori live in a continuously infinite dimensional Hilbert space, will be compressed down to a finite and small number of parameters. This will then allow to solve numerically very generic (non-integrable) strongly coupled theories in a fully non-perturbative manner. Such a compression was long thought to be impossible, in particular in the relativistic case, but I overcame crucial theoretical hurdles in the past year, making the proposal particularly timely.  I will construct this framework with 3 main applications in mind: i) non-relativistic problems in 2 space dimensions and more, including e.g. fractional quantum Hall states, ii) relativistic QFT, starting with 1+1 dimensional toy model and gradually increasing complexity to get closer to nonabelian gauge theories, iii) critical quantum systems (and classical statistical mechanics).

Mots-clés : tensor networks,quantum field theory,variational wave functions,entanglement
Projet ERC : IQ-SCALe (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 1420403.0 €

Since Shor’s seminal algorithm, we know that quantum computers will break deployed public-key cryptography. Fortunately, there are quantum-safe solutions based on objects known as codes and lattices. These solutions were identified by an algorithm of Regev showing that if there is an attack, then a quantum compter will enable to solve problems believed to be intractable. Apart from this result, very few quantum algorithms were designed to assess or to break the security of code and lattice-based cryptography. IQ-SCALe is here to address this gap by opening a new and uncharted area for quantum algorithms.  One of the motivations behind IQ-SCALe is a recent attack I designed against advanced cryptosystems. My attack based on Regev's approach demonstrates that it had not been sufficiently exploited. I also identified tools from Regev's approach to be at the core of a fundamental research area - sphere packing bounds - for which powerful generalizations are known. However, they involve more complicated objects (non-commutative groups) and the analogous quantum tools have not yet been designed.  IQ-SCALe aims to design new quantum algorithms for this broader theory. Historically, Regev’s approach not only enabled us to assess the security of some cryptosystems by identifying an intractable problem, it was also leveraged to mount attacks as I have shown. The new quantum tools that I will design in IQ-SCALe will likewise lead to both the identification of useful cryptographic problems and the design of new algorithms for attacks and proofs of hardness. It will considerably increase our trust in code and lattice-based cryptography.  Current quantum algorithms to assess the security of code and lattice schemes are adaptations to the quantum setting of classical approaches. This will not be the case for innovative algorithms of IQ-SCALe. But beyond algorithms, it will also create new connections between advanced mathematical areas and code and lattice-based cryptography.

Mots-clés : quantum computing,post quantum cryptography,lattice based cryptography,code based cryptography
Projet ERC : EMOBB (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : PI
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 1499681.0 €

Deciding what to do when for how long – self-organizing one’s behaviour – is an important feature of daily life. Emotions arise providing short-cuts for the computational complexities. Yet, we still know relatively little about the underlying cognitive and neural mechanisms. EMOBB will establish the computational, cognitive and neural underpinnings of the rich interplay between emotions and self-organized behaviour in naturalistic environments overcoming three key challenges. First, previous work has almost exclusively relied on tasks structured into experimenter determined trials – thus how people self-organized behaviour could not be measured. To overcome this, EMOBB will combine novel naturalistic tasks in which people have freedom what to do when for how long with subjective and objective measures of emotions. This will be made possible through a computational modelling approach that allows dissecting and quantifying even complex behaviour-emotion interactions. Second, many previous decision-making tasks have limited relevance for real-life cognition and individual differences. EMOBB will address this by relating the computational task measures to individual differences in real-life behaviours and emotional traits. This effort will culminate in the creation of a video game platform providing a large population benchmark. Third, brain imaging has primarily relied on correlations, often focusing on individual regions. EMOBB will go beyond this testing the causal role of brain networks and their shifting compositions to cognitive state changes combining functional magnetic resonance brain imaging and non-invasive ultrasound brain stimulation. While the challenges are important by themselves, combining all aspects in one project will allow a breakthrough in our understanding across all levels from neural underpinning to individual differences. Specifically, it will deliver a model of naturalistic emotion-behaviour interplay and its mediating brain mechanisms

Mots-clés : computational modelling decision making naturalistic tasks cognitive neuroscience functional magnetic resonance imaging transdiagnostic approach brain stimulation computational psychiatry