Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : CRIMLIFE (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université de Marmara — Pays : Turquie — Rôle : Partner
Acronyme de l'entité : MÜ
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 38750.0 €

How do social contexts determine paths into crime? How do these trajectories vary across different societal circumstances? And how are they narrated? CRIMEGLO is the first-ever large-scale comparative life-course criminological study globally. No research hitherto has addressed criminal careers and storytelling in such detail and on the scale envisaged in this project. The approach will counterweight the current Northern bias in research and theory, a shift necessary to establish a truly global perspective within life-course criminology. Cultural and societal contexts play a large role in defining and responding to crime. Social conditions shape the life-courses of those getting caught up in the criminal justice system. Context is also intertwined with the ways people talk about their lives. CRIMEGLO will explore and compare crime from a life-course and life-story perspective spanning four continents and six countries: Norway, the Czech Republic, Türkiye, Nigeria, Bangladesh, and Colombia. By combining criminological theory with institutional, cultural, and narrative studies, CRIMEGLO’s goal is to establish global comparative research on crime within a life-course perspective. The primary objective is to introduce and theoretically develop a contextually sensitive, comparative global life-course criminology. The secondary objective is to achieve a better empirical understanding of the particular social, economic, institutional, and gendered factors shaping criminal life-courses in different countries with highly divergent societal contexts. Principal Investigator Sveinung Sandberg is a sociologist and one of Europe’s leading qualitative criminologists. He has pioneered the prominent research traditions of Bourdieusian Criminology and Narrative Criminology. With CRIMEGLO, he expands globally his qualitative work on life-courses and life-stories started in Latin America and, for the first time, incorporates quantitative and comparative methods to his research.

Mots-clés : sociology,criminology,narrative criminology,life course analysis,life history analysis,crime
Projet ERC : DIGECON (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Fondation Jean-Jacques Laffont - Toulouse sciences économiques — Pays : France — Rôle : PI
Acronyme de l'entité : JJL-TSE
Type d'entité : Recherche
Financement ERC de l'entité : 1443750.0 €

The digital economy is of growing importance for society, but its development challenges the traditional approaches to competition policy and regulation, based on a benchmark of perfect competition that regulatory authorities aim at approaching in the various relevant markets. Economies of scale and scope are more the rule than the exception, network effects and multi-sidedness are pervasive, information and data are shaping industries, the boundaries of the markets are becoming blurred, and industry dynamics are on a new scale. These features make the perfect competition benchmark and the focus on individual markets less relevant, calling for a new conceptual framework for the analysis of competition in the digital economy. The proposed research aims at breaking new ground on four related fronts. First, competition in the digital economy is increasingly between ecosystems involving multiple products and, often, multiple actors. Second, platforms compete for consumer attention, raising questions about consumer behaviour and platforms’ ability to influence it. Third, the digital revolution has drastically affected the way firms compete and cooperate along the vertical chains of production and distribution. Finally, the role of data raises questions not only about the interplay between business strategy and consumer privacy, but also about how the quest for data can shape entry and competition in product markets. On each theme, several avenues are proposed to enhance our understanding of how competition works in the digital era; the insights will shed light on desirable changes for competition policy and regulation – interpreted in a broad sense, including policies that affect the functioning of digital markets such as consumer or privacy protection policies.

Mots-clés : digital economy,competition,competition policy,regulation,data markets,privacy,ecosystems,complements and substitutes,consumer attention,consumer behaviour,business strategy,transaction costs,search costs
Projet ERC : COLDOC (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Université Justus-Liebig de Gießen — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2493529.0 €

This proposal ventures into organic chemical reactions under not-so-common conditions, namely in the cold, at insufficient energies, and under the action of hard radiation. As many organic molecules have been discovered in space or brought to earth in meteorites, they must have formed under such conditions through hitherto largely undisclosed mechanisms. One key hypothesis is that quantum-mechanical tunneling (QMT) and novel reactions with exceptionally low barriers are at work. Hence, one of the key objectives is to uncover how QMT, where reactions occur through and not over barriers, controls chemical reactivity and selectivity. A second goal is the examination of cryogenic reactions of hydroxycarbenes or enols with carbonyl compounds. Our methods include organic synthesis of starting materials (also isotopically labelled) and products, infrared as well as ultaviolet/visible matrix-isolation spectroscopy, ab initio computations of structures, spectra, and potential energy surfaces as well as QMT rate calculations. We will examine isotope-selective reactions of competing QMT reactions that can be made selective through strategic isotope incorporation. QMT also offers new ways to activate carbon dioxide and even to catalyze reactions. We propose a unifying synthesis of carbohydrates and alpha-amino acids through a common mechanistic scenario, namely a newly discovered hetero-carbonyl-ene reaction of carbenes or enols in the gas phase. Finally, chemistry far from thermodynamic equilibrium is explored with probing the activation and reaction of highly stable molecules under irradiation with energetic electrons, thereby mimicking conditions of the interstellar medium exposed to galactic cosmic rays. This should shed light on the formation of larger “complex organic molecules” found in this medium and often considered as building blocks for life.

Mots-clés : physical organic chemistry,quantum mechanical tunneling,tunneling catalysis,matrix isolation,carbenes,prebiotic chemistry
Projet ERC : MissingLinks (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and I mmunotherapy
Entité participante : Université nouvelle de Lisbonne — Pays : Portugal — Rôle : PI
Acronyme de l'entité : UNL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2999625.0 €

The bacterial pathogen Staphylococcus aureus is currently the second most common cause of death associated with antibiotic resistant infections. The most useful antibiotics in clinical use have multiple targets, as compounds against single proteins rapidly succumb to the capacity of bacteria to develop resistance. To think innovatively about antibiotic discovery, we need to think not only about individual cellular processes, but also about how they are interconnected and coordinated, so that we can devise methods to strike bacterial cells, simultaneously, in multiple pathways. The bacterial cell cycle consists of a series of coordinated events required for bacterial growth, during which cells duplicate their mass and undergo chromosome replication and segregation, assembly of the division machinery, cytokinesis, and cell separation to generate two new daughter cells. Unregulated cell cycle progression may have lethal consequences for the cell and therefore bacteria have evolved various mechanisms for the precise spatiotemporal control of main cell cycle events. Some important checkpoints have been studied, particularly the link between chromosome replication/segregation and septum synthesis, to avoid DNA breaks. However, the mechanisms for coordination of other cell cycle events are still unknown. What triggers initiation of peptidoglycan synthesis, the target of beta-lactam antibiotics, after assembly of the division machinery? How does the cell coordinate synthesis of the membrane and peptidoglycan, the two major cell surface components, during cell division? What prevents premature septum splitting, which would expose an immature cell surface, devoid of virulence factors, leading to pathogen elimination by the innate immune system of an infected host? The aim of this project is to find the missing links between major cell cycle events, while also developing assays useful for antibiotic discovery.

Mots-clés : staphylococcus aureus,cell cycle,cell division,antibiotic resistance,flim fret,
Projet ERC : STUFF (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université Justus-Liebig de Gießen — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499711.0 €

Different materials, such as silk, soil, steel and soap exhibit an astonishing variety of physical properties, appearances and behaviours. The material properties of objects and substances are central to practically every task we perform, from selecting and preparing food, to detecting slippery ground, to using tools effectively. Without touching a surface, we usually enjoy a vivid impression of what it would feel like, through the sense of sight. Yet, how we do so remains mysterious. Decades of research has focussed on the visual recognition of objects, faces and scenes. By comparison, how we see, think about and interact with ‘stuff’ has been relatively neglected. STUFF addresses this major gap in our understanding. Material perception poses unique and fascinating challenges. The image of a surface is a complex and ambiguous combination of lighting, shape, and material properties. How does the visual system disentangle these intermingled physical factors? Deformable materials like liquids and textiles move and change shape in complex yet lawful ways. How do we infer intrinsic properties like viscosity, compliance and elasticity from such ever-changing stimuli? And how do we reason about and predict their future behaviours as they interact with their surroundings? How do we adapt our own interactions with objects to take into consideration their hardness, density, friction and other physical characteristics, allowing us to pluck a raspberry without crushing it, or pick up wet soap without it slipping through our fingers?  STUFF takes a radically interdisciplinary approach to these questions in five tightly interconnected work-packages, bringing together state-of-the-art methods from experimental psychology and behavioural neuroscience, computer graphics and computational image analysis, machine learning and even art. We draw on real and simulated materials, to uncover how we perceive, reason about, predict and interact with materials and their properties.

Mots-clés : visual perception,material perception,art perception,surfaces,objects,shape,computational modelling,grasping,action,deep learning
Projet ERC : CollAdapt (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Complexity Science Hub Vienna — Pays : Autriche — Rôle : PI
Acronyme de l'entité : CSH
Type d'entité : Recherche
Financement ERC de l'entité : 3096966.0 €

Human collectives adapt their cognitive strategies and social networks flexibly in response to multiple changing problems. For example, we as scientists continuously revise our teams and the way we integrate information, depending on the topics we study. As citizens, we participate in diverse collectives that use different strategies to address challenges ranging from economic development to climate change. This ability for collective adaptation contributed to our species’ spectacular success, but sometimes our collectives seem stuck and unable to adapt to the problems they face. We currently do not have a solid scientific paradigm for studying collective adaptation, and its cognitive and social aspects have been studied largely independently in different disciplines. I will develop such a paradigm by building computational models to integrate research on cognition and sociality, and by collecting diverse empirical data on the interaction of cognitive and social processes, including group experiments, natural language processing of large textual corpora, and longitudinal surveys. This will allow me to investigate (i) the interplay of social learning strategies, networks, and problems that collectives face, (ii) the formation and persistence of people’s beliefs about what the important problems are, and (iii) the effect on collective adaptation of individual differences in these beliefs. I am well positioned for this task because of my experience in building computational models grounded in theories and data on human cognition and sociality, and the support from the Complexity Science Hub Vienna that has been designed for this kind of research. This project will enable us to understand why collectives can be stuck in deadlocks about important problems and why they sometimes appear incapable of finding seemingly obvious solutions, ultimately helping us to avoid undesirable societal trajectories such as those leading to extremism and violence.

Mots-clés : social learning,belief dynamics,social networks,computational models
Projet ERC : ELUD (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Université technique de Munich — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1539750.0 €

Game theory is essential for studying central problems in economics and management such as auctions, contests, oligopoly, and platform competition. However, deriving equilibrium strategies in such games with incomplete information is notoriously challenging. For instance, analytical solutions are available only for simple auction models under restrictive assumptions. The lack of numerical methods for solving equilibrium problems impedes advancements in theory and practice. Building on insights from my recent research, ELUD develops online optimization and learning methods to solve equilibrium problems in single- and multi-stage Bayesian games that have previously been deemed intractable. These new methods are designed to accommodate a variety of distributional assumptions and utility functions allowing to incorporate behavioral motives and asymmetries among agents. Importantly, learning algorithms also serve as models for artificial agents in real-world agentic markets, such as those for bidding in display advertising auctions and pricing on online retail platforms. Such agents cannot play equilibrium strategies from the start, but they adapt to the market and learn profitable strategies over time. However, learning algorithms do not necessarily converge to an equilibrium in games; they can instead lead to cycles or even chaotic behavior and such phenomena have been observed experimentally in some environments. ELUD allows us to understand the properties of market models under which classes of algorithms lead to an efficient equilibrium and when they do not. This is highly ambitious because ELUD needs to develop new mathematical methods to study the constrained dynamical systems resulting from the interaction of learning algorithms. An extensive set of experiments will complement and aid the theory development. After ELUD, there will be widely applicable equilibrium solvers for important classes of games, and a theoretical framework to analyze automated markets.

Mots-clés : equilibrium learning,operations research
Projet ERC : EPICAL (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université technique de Munich — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2498200.0 €

Intelligent chatbots (ICs) such as ChatGPT have revolutionized the generation of content for a few languages such as English, but there are 7099 currently spoken languages in the world. EPICAL will, for the first time, determine how to add new low resource languages (LRLs) to ICs. We will make six advances to revolutionize the capabilities of ICs, unifying different areas of research that are incorrectly studied separately. We will: 1) determine how to generate hallucination-free text using ICs, and how to enter a virtuous cycle where LRL text is created using cross-lingual knowledge from ICs and then quickly post-edited and trained upon, resulting in a better LRL representation in the IC. 2) develop more powerful encoding and language adaptation approaches which combine the benefits of fine-tuning and adapters, taking full advantage of linguistically related languages to model LRLs. 3) enable ICs to reason about their own LRL capabilities and determine what they know and do not know. 4) unify research on machine translation and ICs to obtain ICs which can translate to LRLs with state-of-the-art accuracy. 5) enable high quality text-to-speech and automatic speech recognition of LRLs with ICs, thereby unifying the research on low resource speech processing with research on LRL text processing. 6) develop a novel evaluation methodology including a robust method for automatically measuring fact hallucination. My research group is well-known for LRL research, which differs from large commercial labs focusing only on the top 200 languages. Our work is critical for a multilingual Europe which values the role of minority languages, culture and heritage. Our innovations will benefit natural language processing beyond text generation and machine translation and strongly impact other areas of machine learning research suffering from data bottlenecks.

Mots-clés : intelligent chatbots,large language models,machine translation,natural language processing
Projet ERC : NanoLPC (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université technique de Munich — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2485500.0 €

Light-induced phase change (LPC) is the unifying theme underpinning many apparently non-related processes in i) additive manufacturing (AM) for metals where laser induced vaporisation and the formation of keyhole porosity is a major limiting factor for 3D printing, ii) nanomedicine (NM) where laser induced nanobubble dynamics and associated shockwave effect is powerful for malicious cell destruction, and iii) solar energy (EN) where direct steam /vapor production from bulk and surface fluid is a promising technology for power and clean water solutions. In addition to the challenging multiscale nature of phase change, LPC add further complexities by introducing the multiphysics nature due to strong light-absorber interactions. We will tackle the fundamental challenge of the formation and control of LPC and develop a physics-based platform, supported by multiscale experimentation and multiscale simulation, as the tool to design and engineer LPC as innovative mechanism for in situ process steering and control. Five work programs are designed focusing on two complementary paradigms: i) fundamental studies for enhancing LPC mechanism understanding via developing physics-informed multiscale modelling validated by dedicated nanoscale experiments, and ii) application studies for engineering LPC for designed functions towards EN, NM and AM respectively. Many breakthroughs beyond state-of-art work are expected, such as i) the establishment of a unique multi-physics and multiscale LPC simulation platform; ii) the revelation of LPC mechanisms by sub 100 nm experiments with localized temperature and nanobubble dynamics measurement; and iii) the reverse engineering of LPC to maximize solar vapor production, inhibit keyhole pore formation and control nanobubble shockwave effects. The project will not only advance LPC understanding in the domain of Thermodynamics and Heat Transfer, but also transfer the developed expertise into emerging applications.

Mots-clés : phase change,nanoscale heat transfer,multiscale simulatioin,solar evaporation,nanobubble,keyhole porosity
Projet ERC : Co-EvoChange (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université d'Helsinki — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Anthropogenic global change is reshaping planetary biodiversity patterns at an accelerating rate. The diverse and non-linear ways in which species respond to global change can lead to non-obvious alterations in the structure and intensity of species interactions. However, the extent to which coevolutionary dynamics are disrupted under biodiversity change remains largely unknown. Interspecific interactions are the key determinants of biodiversity and ecosystem functioning, and their modifications can play a critical role in modulating global change effects on ecosystems. In this proposal I focus on plant-microbe associations to uncover how temporal change in plant communities affects interactions with mutualistic and pathogenic microbes both above- and below-ground. By coupling analysis of plant biodiversity time-series data with contemporary sampling of microbial communities, experiments and molecular assays, this work will demonstrate how both ecological and coevolutionary dynamics of species interactions are responding to ongoing environmental change. Specifically, I will answer the following key questions: 1) How has forest understory vegetation changed in response to changing climate and habitat use over 35 years; 2) How does temporal plant community change affect plant-associated microbial communities; 3) How have the intensity and efficacy of mutualistic and pathogenic host-microbe interactions changed; 4) How is coevolutionary selection, measured as local adaptation, altered following biodiversity change; 5) How do ecological and coevolutionary change underpinning species interactions scale up to ecosystem functioning in plant-microbe communities. The obtained results will reveal how vulnerable both pathogenic and essential mutualistic associations are to global anthropogenic change. Jointly the proposed research provides synthesis of the relative importance of ecological, evolutionary and environmental dimensions of biodiversity change.

Mots-clés : plant microbe interactions,host pathogen interactions,host mutualist interactions,biodiversity change,coevolution,local adaptation,plant ecology,field ecology,experimental ecology