Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SEMANI (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Université Louis-et-Maximilien de Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1580832.0 €

Rising income inequality and related disparities, accompanied by high persistence of socioeconomic outcomes across generations, have become a major public policy concern around the world. Documenting inequality, understanding its determinants, and evaluating policies with the goal of reducing inequality is an important part of empirical research in economics. Widely used statistical tools for quantifying the importance of various drivers of inequality and intergenerational mobility have produced influential findings that are directly, and often informally, interpreted in public and political debates. In these debates, causal and economic meaning tends to be attached to the stylized statistical findings without the use of empirically tested structural models. The first objective of the proposed project is to show theoretically and empirically that these widely used statistical tools generate findings that permit a structural economic interpretation only under very strong assumptions. If these assumptions fail, then the structural interpretation may be misleading, and the findings may not in fact measure what they purport to measure. The second objective is to develop new, robust statistical tools that are guaranteed to produce findings with a structural interpretation while retaining the attractive features of popular existing approaches, e.g., weak assumptions and data requirements.  Through substantive economic applications of the new statistical methods the project is expected to discover powerful new insights about what drives inequality and what are effective policies for reducing it. In addition, it is expected to provide a new interpretation of a vast and hugely influential body of empirical research, which has shaped our understanding of inequality and has informed policy decisions around the world.

Mots-clés : econometrics,causality,difference in differences,partial identification,robustness
Projet ERC : NOMOS (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Université Louis-et-Maximilien de Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999281.0 €

In the crucial half-millennium between the death of the Prophet Muhammad and the First Crusade, an absolutely essential part in the origins of Christian-Muslim relations has been overlooked, namely how the normative regimes of Eastern Christians – including those of Byzantium, the Islamicate world and the space in between – grappled with the rise of Islam. Exploring this history has important implications for our understanding of the development of Christian-Muslim relations in the premodern period, the genesis of Eastern Christian legal regimes and the earlier precedents which Eastern Mediterranean states after the year 1100 might have drawn on in dealing with Islam.  By assembling a corpus of “Saracen law” provisions and utilizing cutting-edge, AI-supported technologies to create new editions of legal texts, NOMOS will examine how, within the realm of normative knowledge, the new religion was interpreted, circumscribed and defined and, moreover, how the encounter with Islam itself shaped long-term developments within Eastern Christian legal regimes. Despite differences in literary language (Greek, Syriac, Coptic and Armenian), levels of statehood (ranging from the Byzantine Empire, the smaller Armenian principalities to the stateless Coptic and Syriac communities) and confessional affiliation (Orthodox, Monophysite or “Nestorian”/Church of the East), the encounter with Islam constituted the most significant factor in the late antique development of each of these legal normative orders in this period. This innovative, legal-historical approach to the history of the early medieval Middle East will not only offer a new way of looking at Late Antiquity in the first centuries of Islam, but will also provide a crucial new narrative of Christian-Muslim relations in the Eastern Mediterranean world before the First Crusade – and thereby problematize the traditional “Western”-dominated paradigm for this history.
Projet ERC : RECC (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : Université Louis-et-Maximilien de Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1997950.0 €

In the prevailing view, cuneiform script survived until the first century CE because it was the only way to write the most enduring Mesopotamian science, astronomy. This view, however, is skewed by the nature of the data: while astronomical texts are easy to date, the vast majority of non-astronomical tablets cannot be dated and are overlooked in histories of the period. Yet, the vitality of cuneiform in its terminal phase suggests that a wealth of late literary and scholarly tablets awaits the development of new dating methods.  The aim of the Rewriting the End of Cuneiform Culture (RECC) project is to explain why cuneiform survived long after the great Mesopotamian centers had lost their prominence and become provinces within vast empires. The hypothesis posits that the survival and flourishing of cuneiform is a reaction to these changes, an attempt to defend the native tradition against cosmopolitan cultures. With their labored writings, Babylonian scholars endeavored to show that their legacy still had the power to speak to their own world. The project has three Research Objectives: • To grasp the extent of the textual production of the late period and the network of scribal families responsible for it. • To chart the development of cuneiform script by means of a pioneering Machine Learning-powered tool (CuneiDate) that enables, for the first time, the inferred dating of undated tablets. • To rewrite the end of cuneiform civilization by explaining the reasons for the continued use of cuneiform.  This pathbreaking method promises to revolutionize cuneiform studies and other disciplines that study manuscript cultures by providing historical context to thousands of unmoored documents. The recovery of these contexts will disclose how the Babylonians coped with the loss of significance of their millennia-old traditions and offer insights for contemporary cultures experiencing “cultural anxiety” as they interact with more dominant cultures in a globalized world.

Mots-clés : cuneiform,mesopotamia,hellenistic babylonia,assyriology,digital paleography
Projet ERC : COGY (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Université rhénane Frédéric-Guillaume de Bonn — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999736.0 €

The foundations of the general theory of relativity (GR) were laid by Albert Einstein in 1915. But much of what has been built on those foundations was developed in the Renaissance Period of GR between 1955 and 1975. Indeed, without the concepts and tools formed during this Renaissance, the recent observation of gravitational waves, rewarded with the Nobel Prize in physics in 2017, and the convincing prediction of and mounting evidence for the existence of black holes, rewarded with the Nobel Prize in physics in 2020, would not have been possible. At the centre of the Renaissance of GR is Roger Penrose. It was Penrose who developed much of the tool box that made the successes of the Renaissance possible. Penrose was surrounded by and built upon the work of the newly emerging international community of relativists, in particular Hermann Bondi at Cambridge, John Wheeler at Princeton, Jürgen Ehlers at Hamburg, and Stephen Hawking at Cambridge. The Centre of Gravity Project (COGY) will combine pioneering research on the literary estates of the core figures of the Renaissance period, including unique access to the hitherto inaccessible Penrose estate, with the analysis of detailed oral-history interviews. The analysis will be helped by the creation of a novel kind of database that will help cross-correlate the different sources. The aim is to get to the bottom of the most advanced mathematical techniques and conceptual innovations of GR, concepts like black holes and event horizons. In understanding the genesis and subsequent interpretation of these concepts we will also lay the groundwork for understanding the most exciting elements of today's physics: the physics of gravitational waves as they arise from black hole and neutron star mergers, as well as of the supermassive black hole around which our entire galaxy rotates.

Mots-clés : integrated history and philosophy of science,history of modern physics,history of recent science,general relativity,gravity,mathematical relativity,black holes,gravitational waves,mathematical methods in science
Projet ERC : Vortex (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : Partner
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 93750.0 €

The main goal of this project is to understand the geometry of the deeply influential topological phase transitions which were discovered in the 70's by Berezinskii, Kosterlitz and Thouless. The archetypal example of such phase transitions arises in the 2d XY model in which topological defects, called vortices, behave very differently at small and high temperature. The mathematical understanding of this rich phenomenon goes back to the work of Fröhlich and Spencer in the 80's and involves the 2d Coulomb gas. This project is aimed at analyzing this phase transition through the prism of random fractal geometry by associating natural percolating sets to the XY model whose behavior will depend crucially on the temperature. One constant source of inspiration will be the deep geometric content and powerful probabilistic methods gathered over the last 20 years for celebrated discrete symmetry models such as 2d critical Ising or percolation. New tools will be brought in, among which the recent works of the PI with Sepúlveda which analyze the 2d Coulomb gas and make connections with Bayesian statistics.  Since the early days of topological phase transitions, topological defects have been found to arise also in some discrete symmetry spin systems as well as in Abelian lattice gauge theory in 4d. This project will explore the geometry of these by making several novel and fruitful connections with the dimer and Ising models.  The new connections made with statistical reconstruction and Bayesian statistics will give access to the even more fascinating and least understood world of spin systems with non-Abelian (gauge-)symmetry. Finally, we shall investigate the mechanisms which relate the microscopic background noise with the large scale structures it induces in the contexts of Quantum Field Theory and KPZ fixed point. The impact of this project will go well beyond the current understanding of topological phase transitions in a wide variety of settings where they arise.

Mots-clés : kosterlitz thouless transition,coulomb gas,xy model,lattice gauge theory,gaussian free field,discrete beta ensembles,kpz fixed point,ising model,critical percolation,dynamical percolation,noise sensitivity,planar statistical physics
Projet ERC : AtomicPIE (Horizon Europe, appel 2025, Consolidator grants)
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 : 1936682.5 €

Inorganic materials are integral to numerous fields, including transportation, electronics, and medical applications. Understanding their mechanical properties, particularly permanent inelastic deformation, has been a central pursuit in material science. My project, AtomicPIE, focuses on uncovering the key mechanisms driving plasticity in metallic alloys, emphasizing dislocation-interface interactions. These interactions occur at grain boundaries and phase boundaries, which significantly influence material strength, reliability, and lightweight properties. Despite extensive studies, a comprehensive understanding of slip transfer—how dislocations propagate across interfaces—remains elusive. AtomicPIE integrates atomistic simulations, generative machine learning models, and enhanced discrete dislocation dynamics to address this gap. By simulating crystalline defects and their interactions, the project employs Nye dislocation densities to bridge atomic- to micro-scale modeling. A key innovation is the use of machine learning to predict complex Nye dislocation fields for mesoscale simulations. The framework developed within AtomicPIE will be validated through experiments and cross-scale molecular dynamics, focusing on ultra-fine-grain aluminum alloys. AtomicPIE aims to establish a physics-based understanding of slip transfer at interfaces, paving the way for advanced materials design and interface engineering.
Projet ERC : BYTE2BITE (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Université Louis-et-Maximilien de Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1110963.5 €

Potato is one of the three most important food crops in the world. Around 1.3 billion people rely on potato as a staple food every day. But despite this exceptional socio-economic importance, the improvement of potato during the past 150 years has been limited. The main reason for this deficit is the highly heterozygous, autotetraploid genome of potato. This complicates several important aspects of breeding including the fixation of beneficial alleles and the implementation of modern, genomics-assisted breeding techniques. Recently it has been suggested to convert tetraploid potato into a diploid crop, and thereby overcome all the difficulties associated with tetraploid potato breeding. However, the creation of diploid potatoes is hampered by the large number of deleterious recessive mutations that have accumulated in the tetraploid genome and are exposed in the diploid potatoes. In BYTE2BITE we will address the fundamental issues that hold back the success of potato breeding. We will generate the first-of-its-kind, near-to-complete pan-genome of potato and use this resource to develop unprecedented genome-graph tools for efficient genotyping and haplotype-resolved genome analysis. We will then use this new computational toolbox to establish a genomics-assisted pre-breeding programme in which we will generate novel potato cultivars with low mutational load. This new resource will open the doors to efficient breeding unleashing the genetic potential of potato and thereby help to secure the way we feed the world for the decades to come.  Specifically, in BYTE2BITE we want to achieve the following goals: 1. A near-to-complete pan-genome describing almost the entire haplotype diversity of potato 2. A genome graph tool for cost-efficient genotyping and haplotype-resolved genome analyses 3. A genomics-assisted pre-breeding programme for potatoes with low mutational load

Mots-clés : pan genomics,plant genome assembly,potato breeding
Projet ERC : CATACLIS (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université Louis-et-Maximilien de Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Cellular therapies are commonly used to treat hematological cancers but have yet to be established in solid oncology. Their evolution has been fuelled by hypotheses derived from cell biological observations in cancer models. Most approaches, however, will either never enter clinical development or fail clinical testing, often due to inadequate models of disease and their lack of relevance to human biology.  In CATACLIS, I propose the first unbiased development of cellular products based on patient characteristics in order to address this enormous translational gap and ultimately provide more effective cell therapies to patients with solid cancers. CATACLIS will herald a paradigm shift in cell therapy by reversing conventional model-to-patient innovation ("forward translation") to patient-generated ideas tested in patient-derived models into clinical trials ("reverse translation").  I have discovered novel approaches to improve T cell function, which resulted in a clinical trial and established me as a leader in the field of cellular therapies. The challenge I will now face is to move beyond model bias and integrate cancer heterogeneity across patients and entities. In CATACLIS, I will use single cell data sets from patients to inform the design of next generation cellular therapies capable of overcoming current limitations in solid cancers, namely 1) access to tumor tissue, 2) target antigen(s) selection, and 3) immune suppression. To maximize clinical relevance, CATACLIS will use patient-derived materials from hypothesis generation to in vivo testing. This will enable me to create cellular products tailored to the patient´s cancer  My research will not only result in novel cellular products for further testing and development toward clinical trials, but it will also serve as a resource for the development of innovative therapies based on patient data, contribute to the European open science objectives, and reduce the burden of animal experimentation.

Mots-clés : computational analysis car t cells chemokine receptors fusion proteins synthetic biology reverse translation
Projet ERC : CancAHR (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Helmholtz-Gemeinschaft — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HGF
Type d'entité : Recherche
Financement ERC de l'entité : 1999925.0 €

The aryl hydrocarbon receptor (AHR) is a critical regulator of tumor progression by modulating both tumor cell intrinsic malignant properties as well as anti-tumor immunity. However, depending on the context, the AHR can exert either tumor-promoting or tumor-suppressive effects, thus limiting its potential as a drug target. To exploit the AHR for cancer therapy a comprehensive understanding of its activation and biological outcomes is necessary. The opposing effects of the AHR in cancer likely stem from the complexity of its activation and biological functions, which are cell type-, ligand-, and context-specific. Moreover, recent results from our laboratory suggest that nutritional stress conditions also affect AHR activity. The detection of AHR activation in tissues mainly relies on the quantitation of AHR target gene expression. However, until recently, the context specificity of AHR target gene expression had impeded systematic investigation of AHR activity across human cancers. Our team has developed a pan-tissue AHR signature that detects AHR activity irrespective of cell type or ligand, and enables the analysis of the biological functions mediated through AHR activation. The combination of the AHR signature with iterative cycles of computational biology analyses and laboratory experimentation puts us in a unique position to investigate AHR activation and its downstream effects. CancAHR will hence systematically delineate how the AHR is activated in cancer, why AHR activation is cell type-specific, and which AHR downstream mediators drive clinical outcomes. The identification of the molecular mechanisms underlying the diverse outcomes of AHR activation in cancer will enable (i) the identification of patients, in which AHR activation contributes to clinical outcome; (ii) the development of clinical interventions tailored to the specific mechanisms of AHR activation; and (iii) stratification of patients to precision therapies modulating AHR activity.

Mots-clés : aryl hydrocarbon receptor,amino acids,metabolism,cancer cell motility,immune cells,transcriptional signature,protein protein interaction,posttranslational modification,epigenetics,predictive biomarker,therapeutic target
Projet ERC : TAIPO (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Helmholtz-Gemeinschaft — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HGF
Type d'entité : Recherche
Financement ERC de l'entité : 1999225.0 €

Modern machine learning algorithms have the potential to accelerate personalized medicine in a fast pace. To date, first tasks in medicine are being addressed with machine learning algorithms that surpass humans in terms of accuracy and speed, including diagnosis, outcome prediction and treatment recommendation. However, for a widespread adoption in clinical practice, a good performance in terms of speed and accuracy is not sufficient: practitioners also need to be able to trust a model’s prediction in all stages of its life cycle. I will facilitate an efficient interaction of clinicians with AI models by developing trustworthy AI tools for personalized oncology: First, I will develop trustworthy AI tools and algorithms for diagnosis and stratification of cancer patients. Second, I will establish a framework for reliable and transparent modelling of personalized outcomes and therapy decisions in oncology. TAIPO will result in novel algorithms and software tools for quantifying and improving the trustworthiness of AI models that I will apply to three clinical applications: (i) trustworthy AI-based skin lesion classification based on dermoscopic images, (ii) stratification and personalized outcome modelling for patients with acute myeloid leukaemia (AML) based on omics data, and (iv) therapy recommendation for metastatic breast cancer patients based on electronic health records. TAIPO will increase the throughput of trustworthy diagnoses of skin lesions and pave the way for low-cost access to diagnostic care. It will empower clinicians to make personalized and reliable therapy decisions, which we will demonstrate at the example of AML and metastatic breast cancer. Our novel algorithms to evaluate and improve the reliability of AI models are a crucial contribution to close the gap between in-silico AI-bench and bedside and will further push the field of trustworthy machine learning with many applications of AI in medicine.

Mots-clés : machine learning,trustworthy ai,patient stratification,predictive medicine,diagnosis