Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : MechanoResistance (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de Chypre — Pays : Chypre — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Cancer progression is closely associated with generation of mechanical stresses that cause the compression of tumor vessels, drastically reducing delivery of drugs. My co-workers and I found that host cells and extracellular matrix in tumors generate these stresses. Furthermore, we identified the anti-hypertensive losartan to alleviate intratumoral stresses and decompress vessels, allowing drugs to enter the tumor. My colleagues tested losartan in pancreatic cancer patients and found improved responses to chemo-radiation. Nonetheless, losartan cannot alleviate all stresses, and my preliminary data indicate that they induce chemotherapy resistance (“mechanoresistance”). Thus, even though vessel decompression facilitates drugs entering the tumor, mechanoresistance renders cancer cells insensitive to drugs. Alleviating mechanoresistance is an urgent clinical need, but this mechanism has not been well studied and strategies to overcome it have not been developed successfully. To address this challenge, I will employ a mixture of cutting-edge bioengineering and biology methods to identify the intracellular mechanisms that promote mechanoresistance, using in vitro and mouse models of pancreatic cancer. I will then employ inhibitors/drugs of the identified mechanisms to overcome mechanoresistance in vitro and in vivo to determine if they increase the efficacy of chemotherapy. I will also confirm whether these drugs work more effectively with losartan or alone. Using the best performing regimen, I will assess the immunological effects and efficacy in combination with immunotherapy, which has yet to induce a benefit in pancreatic cancer trials. In parallel, in order to take this ground-breaking goal of improving pancreatic cancer therapy to the clinic, I will examine the existence of the same mechanoresistance mechanisms in human tumors. The project will introduce novel, patient-specific, therapeutic strategies to directly boost clinical trials in pancreatic cancer patients.

Mots-clés : bioengineering,biomechanics,mechanobiology,tumor microenvironment,drug resistance,animal tumor models
Projet ERC : ROMANA (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : Université hébraïque de Jérusalem — Pays : Israël — Rôle : PI
Acronyme de l'entité : HUJI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

ROMANA aims to unveil the ubiquitous presence of Rome in Jewish, Greek-Pagan and Christian texts and to expose the strategies of cultural interaction between imperialist forces and a range of minority groups. It will explore how intellectual discourses that have defined the West, namely those of Greek elites, Christian groups, as well as Hellenistic and rabbinic Judaism, were constructed through a series of contested, hidden, and disavowed interactions with the dominant force of empire. The project will redraw the traditional map of the Roman Empire to challenge its sharp dichotomy between Rome and the provinces and demonstrate the deep entanglements of each group of “provincial” elites despite their claim to cultural purity. The starting point is first-century Hellenistic Judaism, as its main representatives—Philo and Josephus—became active in Rome as prolific authors writing in Greek, who combined philosophical, literary and legal interests with a keen appeal to Roman audiences. Their modes of acculturation will serve as a compass to unlock similar cultural entanglements in the Second Sophistic, early Christianity and rabbinic literature. The project objectives entail a focused study of three trajectories, philosophical, literary and legal, to be exposed as doubly entangled, namely with each other and with Roman discourses. The method will be a close, comparative and culturally aware reading of whole corpora of texts in Greek, Hebrew/Aramaic and Latin, based on the available manuscripts, moving through Greek-Christian writing into Rabbinic Judaism and the texts that contest the space between them. We will reach insights of a new order in fields which have thus far been overwhelmingly studied in double isolation or on the limited basis of digital searches of keywords. The results will be published in 6 monographs, special issues in leading journals, a consultation at an international conference and wide dissemination in Israel, up to changes in school curricula.

Mots-clés : philosophy,literature and law,culture and religion in the roman empire jews,pagans and christians
Projet ERC : MEMORAT (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Université hébraïque de Jérusalem — Pays : Israël — Rôle : PI
Acronyme de l'entité : HUJI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2497500.0 €

How much can we remember and for how long? Decades of key advances in our understanding of synaptic plasticity resulted in a puzzle. On the one hand, memories can be highly stable and organisms are capable of adding new memories without destroying old ones. On the other hand, data and models support neither stability nor lifelong (‘continual’) learning. Many experiments suggest that responses of neuronal populations slowly but inexorably drift (“representational drift”), while synapses spontaneously turnover. At the same time, models predict that memory traces of new experiences tend to interfere destructively with old traces. Here, I will study auditory continual learning in the behaving rat. I will develop a novel behavioral paradigm that will train rats to recognize two new sounds every few days, memorizing up to 100 sounds over 3-4 months of continuous training, and check the stability of memory during that time. My lab will apply state-of-the-art recording techniques in order to document the neural activity during memory acquisition and between training sessions while the rats sleep and consolidate newly acquired memories. I will repeat these studies in a rat model for Alzheimer’s disease, which expresses early memory deficits. These results will be compared with predictions of models for memory in the auditory cortex. At one end, I will test the predictions of a model, based on recently published results, that posits the existence of a few neurons that carry the memory of each learned sound by intrinsic bursting. At the opposite end, I will test predictions of models in which memory resides in the coordinated activity of large, distributed ensembles of neurons. Overall, this project will address the deep puzzles of memory when memory load is high, a regime that has not been studied in animal models.
Projet ERC : ELISA (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Université Côte d'Azur — Pays : France — Rôle : PI
Acronyme de l'entité : UniCA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2288712.5 €

This ERC project addresses mathematical theories and numerical tools for mean-field models, which are used to describe the statistical state of a population. Mathematically, such models are often seen as time-dependent systems whose state variable takes values in a space of probability measures. One of the key features of the ERC project is its focus on mean field models for which the state of the population is itself random. Primarily, we aim to consider dynamics with values in the space of probability measures that are subject to an external noise, which is often called a common noise. Our main hypothesis may be formulated as follows: It is possible to construct a common noise that would force mean-field dynamics to explore the space of probability measures in an efficient manner, very much in the spirit of a Brownian motion in the Euclidean setting. This hypothesis will be studied along the following three axes: 1) Exploration is used for forcing uniqueness and stability of solutions to Fokker-Planck and related McKean-Vlasov equations and also to mean-field models of rational agents like mean-field control problems or mean-field games; 2) Exploration is used for the numerical analysis and the statistical learning of mean-field models featuring some optimisation criteria; 3) Exploration can be subject to a more irregular noise than a Brownian motion in the spirit of rough path theory. Expected applications are in probability theory, partial differential equations, control and game theory, optimisation, mathematical modelling and numerical methods at the interface with machine learning.

Mots-clés : mean field models mean field control mean field games noise on the space of probability measures measure valued processes wasserstein diffusion gradient descent on the space of probability measures numerical methods machine learning rough paths
Projet ERC : PANDORA (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : Université Côte d'Azur — Pays : France — Rôle : PI
Acronyme de l'entité : UniCA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2144646.0 €

The Earth's geosphere, hydrosphere, atmosphere, and biosphere have co-evolved together as a single planetary system for billions of years, resulting in a complex web of systemic interactions that have shaped the geological record and biodiversity. However, the complexity of these interactions and the incomplete geological record make it impossible to replay the tape and fully explore the profound mechanisms at play. Here I propose to uncover how mantle convection shapes with the evolution of both the surface environment and photosynthetic autotrophs. To accomplish this ambitious objective, I will construct advanced 3D spherical virtual terrestrial planetary systems operating at geological time scales. I will explore the responses of global coupled carbon-climate-surface process-eco-evolution models to cutting-edge 3D spherical geodynamic scenarios over 1 Gy time-scale. The utilization of these innovative models will resolve a series of fundamental questions such as: what planetary properties drive fast adaptive radiation? What mantle/lithosphere properties generate stable/variable environments over geological time? Throughout this groundbreaking project, I will leverage the power of in silico simulations to create self-consistent virtual terrestrial planetary interiors capable of generating conditions conducive to the evolution of geological and biological diversity. To decipher the intricate relationships between model parameters and their effects on geological, climatic, and biological changes, I will employ state-of-the-art machine learning classification methods. With Pandora, I am poised to make significant strides in understanding the systemic dynamics behind the profound planetary changes that have shaped Earth and potentially other planetary bodies.

Mots-clés : numerical modelling,mantle convection,plate tectonics,climate modelling,surface process modelling,eco evolution modelling,earth system
Projet ERC : PHYSBIOMAT (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université Gustave Eiffel — Pays : France — Rôle : PI
Acronyme de l'entité : UGE
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Bio-based construction materials are air-fiber systems, such as wood, hemp, cellulose, flax, etc., possibly coated with a mineral paste. They represent a promising solution for carbon emission reduction, due to their low production cost and their partial or full recyclability. Moreover, they bring more comfort to the occupants thanks to their moisture-buffering capacity, and they require less energy for heating or cooling. These qualities are obtained through exchanges between water vapor and “bound water”, i.e., water absorbed in the solid structure, combined with heat transfers. Consequently, understanding and predicting water and heat (hygrothermal) transfers in such materials is essential to selecting them appropriately, adjusting their conditions of use, and designing innovative materials. However, the current analysis of their performance is generally based on limited evaluations at a global scale or via macroscopic models lacking physical information. My idea is instead to open the black box and start from the fiber scale, to explicitly describe the internal physical processes at this scale, including sorption dynamics, bound water diffusion, fiber configuration, etc., and then to progressively complete and extend this approach to full-scale materials. This can be used to build for the first time a generic description, understanding, and modelling, of hygrothermal phenomena in bio-based construction materials. This physical description will be supported and enriched by several experimental innovations. Notably, internal measurements of the spatial distribution of moisture content and temperature in time will be obtained from non-invasive time-resolved magnetic resonance imaging (MRI), which can be used to validate the models and determine diffusion properties in an unequivocal way. Finally, I will develop an open-source software predicting hygrothermal characteristics and performance based on material characteristics and history of ambient conditions.

Mots-clés : hygroscopic materials,moisture transfers,heat transfers,nmr,mri,modelling
Projet ERC : PRICOM (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Helmholtz-Gemeinschaft — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HGF
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499286.0 €

A large number of important domains - such as fast moving consumer goods and personalized medicine - have still not seen the benefits of computing, mainly due to high production costs of rigid silicon technologies. Printed electronics based on additive manufacturing processes holds promise of meeting cost and conformity needs of such applications. However, the realization of traditional digital processor architectures is infeasible due to constraints of low-cost manufacturing, such as form factor, low device count, large feature sizes, and high variations. The fundamental research question, hence, is how to perform accurate, reliable and energy-efficient classification computing to meet target applications’ requirements within the constraints of additive printed manufacturing. The aim of PRICOM is to make breakthroughs by developing unconventional mixed-signal classifier computing paradigms together with their hardware realization and mapping based on additive printing technologies. This enables to significantly reduce the hardware footprint, and directly process analog sensory inputs while achieving high classification accuracy. Nevertheless, it is a major challenge as analog computing is very sensitive to variations, and at the same time additive manufacturing is inherently prune to printing variations. I aim at closing this gap by 1) utilizing the inherent tolerance of neuromorphic computing to variations with special hardware primitive design and training algorithms, 2) designing novel variation-aware physical design algorithms, and 3) developing an iterative tuning flow exploiting unique features of additive manufacturing. The feasibility of multi-disciplinary research of PRICOM is underpinned by my unique cross-layer expertise and will be tested by fabrication-based demonstration of printed computing systems. PRICOM can enable proliferation of computing in consumer market and personalized medicine, bringing economical gains and improving quality of life.

Mots-clés : machine learning classifier hardware,printed electronics,resource constrained machine learning,electronic design automation,physical design,neuromorphic computing,computer architecture,design space exploration,reliable computing
Projet ERC : EmQ (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Université technique de Vienne — Pays : Autriche — Rôle : PI
Acronyme de l'entité : TU Wien
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Emergence is central to our understanding of the world. It addresses the question of how did a seemingly unlimited diversity emerge from a small number of simple constituents. Ultimately emergence in physics is related to an inaccessibility of knowledge about the microscopic world, out of which new phenomena are formed at a larger scale. In quantum physics the Renormalization Group is a prominent example relating microscopic physics to emerging new phenomena. The main thrust in the research proposed here is to experimentally study in full detail emergence in the quantum world, all the way from the microscopic physics of elementary (atomic) constituents to a hierarchy of effective models at large scales. A central objective will be to verify emerging models, probe the limits of their validity, when do they break down, and investigate how big a system has to be to show emergent phenomena. Ultra-cold atoms allow to implement and study complex, interacting quantum many body systems in detail and powerful manipulation techniques combined with the ability to measure each atom with close to unit efficiency offers an unprecedented way to probe the whole path of emergence from micro- to macro physics We will investigate three examples: (i) Emergence of quantum field theories as illustrated by the sine-Gordon model; (ii) emergence of universality as the system forgets its initial conditions in the course of non-equilibrium evolution; (iii) emergence of a hydrodynamic description in the non-equilibrium evolution of correlated quantum systems. We envision robust, verified emergent models to have numerous applications as quantum simulators ranging from solid state physics to aspects of physical system that are inaccessible for direct experiments. Moreover, emergence coming from inaccessibility of knowledge about the microscopic world may ultimately lead to a natural bridge between quantum and classical.

Mots-clés : emergence in quantum physics,quantum simulation,experimental models for quantum field theories,emerging hydrodynamics,measuring,probing and verifying quantum systems
Projet ERC : ECHo-LE (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Helmholtz-Gemeinschaft — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : HGF
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 356381.0 €

The discovery of the neutrino mass scale is a milestone for shaping the extension of the Standard Model of Particle Physics. Experiments looking at the endpoint region of low energy beta decay and electron capture spectra benefit from a clear signature of massive neutrinos which only depends on energy and momentum conservation. Along with the well-established use of tritium, as in the KATRIN experiment where the present best limit of 0.45 eV at 95% CL was reached, two collaborations, ECHo and HOLMES have pioneered the use of Ho-163. In both experiments, low temperature microcalorimeters enclosing the Ho-163 source are used. Both collaborations have demonstrated the suitability of Ho-163 for a large experiment. The project ECHo-LE (ECHo-Large Experiment) will be built on the hardware and on solid results obtained with the ECHo experiment and will feature large arrays of metallic magnetic calorimeters where each detector encloses Ho-163 for an activity of 10 Bq. A new cryogenic multiplexer which ensures a homogeneous performance will be used for the readout. On-line data reduction and will be developed to allow for a limited saving space. Following the data analysis developed for the ECHo experiment, new fitting procedures will be tested to reduce the effects of systematic uncertainties. The experiment, consisting of 20000 detectors with gaussian detector response having full width at half maximum of less than 5 eV, will be built in the first two years of the project. After installation, the experiment will run for at least two years. The goal is to acquire more than 10 billion Ho-163 events. The analysis of the data will allow for significantly improving the knowledge of the Ho-163 spectral shape parameters and clearly search for an effect of a finite neutrino mass. ECHo-LE will be the first Ho-163 based experiment able to reach sub-eV/c2 sensitivity on the effective electron neutrino mass and set the basis for the ultimate Ho-163 based experiment.

Mots-clés : neutrino mass,ho 163,low temperature microcalorimeters
Projet ERC : CRYPTONIT (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 2296344.19 €

Silicon (Si) photonics stands as a solid candidate to address the scaling challenges of emerging communication systems with an ever-growing number of interconnected devices. However, Si has major physical limitations that prevent on-chip integration of key functions: strong two-photon absorption limiting nonlinear optical devices, Si centrosymmetry preventing fast optical modulation, and an indirect bandgap nature hindering light emission and amplification. The common solution to overcome these limitations is the hybrid integration of various materials on Si, each addressing one specific limitation. However, this strategy requires a dedicated technology for each material to be integrated, which compromises cost and scalability. In this context, the CRYPTONIT project will explore a new paradigm for Si photonics based on the hybrid integration of multifunctional zirconia-based crystalline oxides (c-oxides), providing several physical properties non-existent in Si: strong nonlinearities, ferroelectricity and light amplification. The original idea is to develop hybrid superlattices, comprising multiple nano-scale layers of different c-oxides to combine key optical functionalities, using a common Si-compatible fabrication process. The project will focus on the demonstration of advanced nonlinear and optoelectronic devices on Si, operating in the near-infrared for the development of highly-efficient and broadband photonic integrated circuits. The main objectives are: i) The development of a hybrid Si photonics platform based on multifunctional c-oxide superlattices; ii) The demonstration of high power and broadband frequency comb sources (strong nonlinearities and amplification); and the demonstration of high-speed >100 GHz optical modulators based on Pockels effect (ferroelectricity). These objectives are ground-breaking in nature and will open new horizons for research and applications in communications, sensing, and quantum photonics.

Mots-clés : silicon photonics,hybrid integration,crystalline oxides,photonic devices,pockels effect,optoelectronics