Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SINOFANTASY (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : Université de Fribourg-en-Brisgau — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1419850.0 €

Fantasy fiction is one of the most understudied areas in in the field of contemporary Chinese literature, a gap that is particularly striking given the current popularity of genres such as Eastern fantasy, science fiction, and silk punk. Over the past two decades, Chinese fantasy fiction has undergone both a quantitative surge and a qualitative transformation, evolving from a niche youth subculture into a fixture of everyday cultural life. The popularity of fantasy fiction reflects not only its mass market appeal, but also its importance in mediating contemporary debates. As a result, fantasy fiction has become a central focus of China’s soft power ambitions, but also one of the most closely monitored areas of cultural production. SINOFANTASY is the first comprehensive study to explore this thematically diverse, immensely popular, and politically sensitive literary field. Current research on fantasy fiction in China is skewed towards media analysis and often dismissive of the genre’s formulaic aesthetics and alleged disengagement from socio-political realities. Within fantasy studies there is also a strong bias towards science fiction, which has a critical pedigree in the West and addresses issues in a more realist key. SINOFANTASY addresses these knowledge gaps and biases by developing a novel, integrative approach to Chinese fantasy fiction and its role within a censored media landscape. In doing so, SINOFANTASY also makes a vital contribution to the global history of fantasy fiction. SINOFANTASY has three main goals that address the meaning, embedding, and agency of fantasy fiction:  1) to develop a historically embedded and theoretically sophisticated account of contemporary Chinese fantasy fiction;  2) to study the relationship between fantasy fiction and key socio-cultural and political developments and debates of the postsocialist period;  3) to analyze the role of fantasy fiction and practices of fantasy fandom within the wider Chinese mediasphere.

Mots-clés : chinese literature,fantasy fiction,science fiction,new media,fan culture
Projet ERC : STEMCELL (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : Université technique de Munich — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Trees play a key role in regulating the global terrestrial water and carbon cycles by controlling water loss through leaves and directing carbon into stems to form wood. In doing so, forests capture substantial amounts of anthropogenic carbon, a crucial process shaping international climate mitigation policies. However, increasing atmospheric and soil water deficits have raised global concerns about the resilience of wood formation in European forests. Predicting how environmental changes will affect wood formation and related ecosystem services remains difficult due to unclear underlying mechanisms. Recent studies identify turgor as a critical link between tree water-use strategies and wood growth, providing new insights into tree responses to water stress. Before application, this concept must be tested, validated, and integrated into forest growth and carbon models.  STEMCELL aims to uncover the relationship between whole-tree water use and wood cell formation in mature trees, using turgor-driven growth models to predict the future of wood formation and carbon allocation in forests facing drier conditions. STEMCELL will integrate experimental, observational, and modelling approaches. Controlled experiments on juvenile trees will be scaled up to mature trees at unique whole-ecosystem rainfall exclusion experiments, carefully monitoring wood formation. These experiments will drive the development of a new numeric model simulating wood formation responses to drought, validated using one of Europe’s largest databases of tree growth, wood structure, and water use.  Through the outlined work, STEMCELL will build a solid physiological and mechanistic foundation for predicting the effects of climate change on wood formation and the global carbon cycle. Given the ecological and economic importance of forest ecosystems, the project's outcomes will be critical for guiding science-based forest management and conservation efforts aimed at strengthening ecosystem resilience.

Mots-clés : mechanistic modelling,carbon allocation,global carbon cycle,forest ecosystems,tree physiology,xylogenesis,drought
Projet ERC : HeliECat (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université technique de Munich — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1486906.0 €

Converting carbon dioxide, an unwanted by-product of industrial processes and combustion engines, into valuable chemical compounds is key for a cyclic carbon economy and can be achieved by the electrochemical CO2 reduction reaction (CO2RR). Despite the immense importance of this reaction in the fight against climate change, no catalyst to date meets the industrial requirements for product selectivity and catalyst stability. Theoretical models and simulations have played a fundamental role in the understanding of these and similar catalytic processes and aided the development of more efficient catalysts for this reaction. These models, however, assume few often idealized surface structures, ignoring the fact that a variety of structures is present under working conditions that define the catalyst properties in terms of efficiency, selectivity, and stability. With HeliECat, I will for the first time establish an approach that offers a holistic view of the catalytic processes, including side reactions and degradation mechanisms. To achieve this ambitious goal, I will combine an efficient semiempirical model for structural exploration with accurate embedded cluster models for kinetic studies. This combination shifts the focus from idealized structures to the diversity of the catalyst surface under realistic conditions. I will then model the interconversion of accessible surface structures with deep reinforcement learning techniques. The analysis of the emerging connected kinetic reaction networks will ultimately allow me to simultaneously study the catalytic activity, stability, and selectivity in silico. I will study the CO2RR on a Cu/Au catalyst surface and demonstrate that automated kinetic modeling, considering structural diversity and realistic thermodynamic boundary conditions, is the key to a predictive simulation of catalyst behavior under actual working conditions. HeliECat will hence pave the way for realistic in silico catalyst screening.

Mots-clés : electrolyte solvation,machine learning
Projet ERC : MOVIOLA (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : École polytechnique fédérale de Lausanne — Pays : Suisse — Rôle : PI
Acronyme de l'entité : EPFL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499329.0 €

The developing nervous system generates an extraordinary diversity of cell types through a series of critical fate decisions made by neural progenitors. Despite recent progress in cataloging the heterogeneity of brain cells, we lack an understanding of the factors orchestrating their fine specification, especially in humans. As a result, many decision processes have uncharacterized determinants and are accounted for as stochastic, leaving us without control over them. This knowledge gap stems from the absence of a systematic approach to capture dynamic moments of cell decision-making and discover the factors controlling them. I hypothesize that most fate decisions in the human developing nervous system are not stochastic and, instead, depend on many fine-grained, dynamic mechanisms of cell decision-making. However, only a limited number have been characterized, too few to explain the thousands of cell types in the human brain. To explore this hypothesis, I propose a novel experimental paradigm to elucidate the molecular determinants governing cell decisions. The approach combines live-cell Raman spectrometry imaging, omics profiling, and inducible degrons. I designed it to operate on cell decisions like a film-editing machine, a Moviola: from an outcome, it learns how to “rewind” to a cell’s decision, “halts” the cell and profiles it for decision determinants, and “edits” it to steer it away from the original outcome. By applying this approach, we expect to find factors influencing fate decisions in human neural specification and reveal a more deterministic control of neural cell fates, illuminating how the vast cellular diversity originates from decision-making events. The insights gained will offer ways to improve in vitro models and cell therapies, with potential implications in the attenuation of neural disorders. This groundbreaking paradigm revolutionizes the study of cell decision-making, with far-reaching implications across diverse fields of biology.
Projet ERC : SYNAPTA (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : École polytechnique fédérale de Lausanne — Pays : Suisse — Rôle : PI
Acronyme de l'entité : EPFL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499130.0 €

“Given the complex, and multifactorial nature of neurodegenerative pathophysiology, strategies aimed at the synapse could provide a useful addition to the therapeutic toolbox” – this quote by B. Dejanovic et al. published in Nature Reviews Drug Discovery this year, highlights the critical need for innovative tools to probe synaptic function. Synapses, where neurons communicate, are tightly regulated by astrocytes, which manage their energy needs (neuroenergetics). Astrocytes shuttle neuroenergetic molecules (e.g., glutamine, lactate, and adenosine) to meet energy demands. Disruptions in these astrocyte-mediated pathways are now recognized as common features in neurodegenerative disorders, suggesting that impaired neuroenergetics may be at the origin of such diseases. Understanding neuroenergetics is crucial for developing therapies that target the root cause of neurodegeneration, not just its symptoms.  SYNAPTA aims to fill this gap by developing nanoscale biosensors that detect multiple neuroenergetic molecules at synaptic dimensions. To achieve this ambitious vision, we will: 1) isolate receptors (DNA aptamers) that reversibly capture neuroenergetic molecules, 2) create a library of DNA aptamer-based biosensors with ~10 nm spatial resolution, 3) design multiplexed sensors, 4) integrate these biosensors into scanning ion conductance microscopy (SICM) and electrophysiology platforms to enable 5) high-resolution, real-time chemical and electrical mapping of synaptic activity. This system will enable millisecond recordings of neuroenergetic molecules at <10 nm resolution, surpassing current technologies. Led by my multidisciplinary expertise in aptamer discovery, chemical biosensing, and neural interfaces, SYNAPTA will consolidate these fields to uncover how astrocyte-neuron interactions affect synaptic function and disease progression. SYNAPTA will advance our understanding of neurodegenerative mechanisms and open new possibilities for therapeutic interventions.

Mots-clés : dna aptamers,nanoscale biosensors,selex,scanning ion conductance microscopy,brain slices,neuroenergetics
Projet ERC : RESIST (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Université technique de Munich — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 833442.5 €

Providing food security in the face of climate change and increasingly frequent extreme heat and drought events is one of the greatest global challenges. Drought is the most influential environmental factor limiting crop yields for a growing world population and leading to significant economic losses. To safeguard agricultural production, it is crucial to develop high-yielding crops with improved water use efficiency. Oat (Avena sativa L.) is an emerging crop that offers significant benefits for human health and provides a nutrient-rich plant-based protein source with a low carbon footprint. However, oats are sensitive to drought and progress in breeding drought-resistant varieties, while urgently needed, is limited. The oat genome is characterised by its enormous size, high repeat content, and complex polyploid structure. Therefore, efforts to investigate complex agricultural traits such as drought stress resistance have long been hampered by the lack of genomics resources. Recently, a fully annotated reference genome sequence of Avena sativa became available, to which I contributed significantly, representing a fundamental breakthrough. RESIST will take on the challenging high-priority task of deciphering the molecular basis of drought stress resistance in oat, providing substantial solutions to secure yields of this emerging, healthy and versatile crop. To this end, RESIST will exploit innovations in plant genomics and in particular oat genetics, employ cutting-edge high-throughput phenotyping methods and establish gene editing protocols that provide an innovative basis for accelerated and targeted breeding of oats. RESIST provides the indispensable foundation for the development of better-performing oat varieties under drought conditions to secure oat yields as a sustainable source of a highly nutritious, healthy, protein-rich plant-based diet for billions of people.

Mots-clés : drought,oat,cereals,health,breeding barriers,gwas,phenotyping,genomics,comparative genomics,pangenomics,computational biology,transcriptomics,gene editing
Projet ERC : CODAC (Horizon Europe, appel 2021, Starting 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 : 1498125.0 €

The goal of this project is to commoditize large-scale data analytics in the cloud, which means (a) to reduce query processing cost to close to what the available hardware is theoretically capable of and (b) to prevent vendor lock-in by making it easy to move data between different clouds and systems. To achieve this, we will design and develop an open and cost-efficient analytical database system for the cloud called CODAC.  The CODAC system consists of three main components: First, an intelligent control component that automatically and transparently selects and manages the cheapest hardware instances for the given workload and makes migration to other (e.g., European) cloud vendors possible. Second, a highly-efficient and scalable query processing engine that is capable of fully exploiting modern cloud hardware. Third, a data lake storage abstraction based on open data formats that enables cheap storage as well as modularity and interoperability across different data systems. The resulting system therefore has the potential for making large-scale data analytics both cheaper and easier, boosting data-driven instruct and science.

Mots-clés : cloud,cost efficiency,data analytics,query processing,data management
Projet ERC : PhotoLanZyme (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Université technique de Munich — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Enzymes are efficient and selective biocatalysts. They are in high demand in chemical and pharmaceutical industry, as they facilitate more sustainable production processes. However, it remains challenging to develop novel enzymes that catalyze reactions beyond nature's synthetic repertoire. To tackle this problem, I propose a fundamentally new approach that merges metal-dependent chemical photocatalysis with enzyme engineering. Photoexcitation is a powerful catalytic tool. It enables alternative modes of substrate activation by generating radical intermediates. Controlling these reactive species to confer regio- and stereoselectivity, however, is a major challenge in synthetic chemistry. The key idea of this proposal is thus to perform photocatalytic reactions inside the chiral environment of artificial metalloproteins, which can be optimized efficiently by directed evolution. My group recently established the formation of lanthanide-protein complexes from highly stable, computationally designed protein scaffolds. Based on this work, we now aim to engineer a photoenzymatic platform for synthetically valuable chemistry. The main goal is to implement and optimize lanthanide photocatalysis in these proteins to facilitate stereoselective C-H activation and C-C bond forming reactions. Moreover, a fundamental mechanistic understanding how such new photocatalytic function emerges in proteins will be crucial for enzyme engineering. To that end, I propose a strategy that mimics natural evolution in a two-step process. Starting from libraries of naive small proteins, a high-throughput screen will first identify lanthanide binders, which are then exposed to a selection system that couples the survival of a bacterial host to an enzymatic detoxification reaction. PhotoLanZyme will yield a new class of sustainable and stereoselective photobiocatalysts. The approach is transferable to other photoredox-active metals, emphasizing its broad potential for synthetic applications.

Mots-clés : artificial metalloenzymes,photoredox catalysis,photo biocatalysis,directed evolution,stereoselective c h activation,stereoselective c c bond formation,enzyme design,protein engineering,lanthanides,cerium photocatalysis
Projet ERC : SemaSign (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université d'Hambourg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1490840.0 €

Words in sign languages are rich in visual meaning. They contain shapes, movements, relations in space, etc. that depict objects and actions as symbolic metaphors; e.g., the action of pulling words out of the head in one language means ‘to ponder’. Yet, signs are also encoded into units of form that are articulated in simultaneous constructions, unlike sequences of consonants and vowels in spoken words. How, then, do signers store richly symbolic words that occur in highly simultaneous forms in their mental lexicons? At present, insight into these mental mappings remains highly occluded, not only at the level of behavioral and neural phenomena, but in terms of linguistic analysis as well. What, indeed, is morphology in sign languages when even the smallest units of form—like hooked fingers or a location at the throat—can carry meaning? What is the nature of these units? Do they vary across sign languages or are the iconic roots of form-meaning mappings so powerful that the same ones re-occur across unrelated sign languages? Answering these questions is urgently needed to create better sign language resources for teaching and learning, and to advance language technologies.  The SemaSign project proposes a ground-breaking approach to these questions by locating form-meaning correspondences in sign languages through computational means while creating new empirically-robust datasets to reveal how signs are organized in the mental lexicon. Semantic networks are created for sign languages from Germany, Kenya, and Guinea Bissau on the basis of word association responses in which a signer sees a sign from their language and responds with the first three signs that come to mind. This will establish an objective measure of semantic relatedness, enabling computational means to locate clusters of signs unusually close in both form and meaning. As the language in Guinea Bissau was formed only 15 years ago, we will also discover how lexicons emerge and grow at a very early stage

Mots-clés : word associations,sign language,mental lexicon,emerging languages,lexical semantics,network science,morphology,cross linguistic,phonology,entropy,phonesthemes,sound symbolism
Projet ERC : EFFICACY (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université de Zurich — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UZH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Chemists constantly seek better catalysts that improve performance of desired chemical reactions and suppress the formation of adventitious products. On the other hand, Nature performs difficult reactions using tailored electric fields as catalysts, and so can we! The overarching goal of this project is to impose, measure and utilize microscopic electric fields to fundamentally understand their organization and elucidate their role in driving non-redox chemical reactivity and catalysis. EFFICACY uses the electric double layer at polarized solid-liquid interfaces to impose strong microscopic electric fields. Despite significant advances in measuring fields projected onto marker vibrational modes (vibrational Stark effect), gaining understanding of the topological complexity (directions, spatial variation) of the three-dimensional electric field vector with Angstrom resolution in its dynamic evolution remains a formidable experimental challenge. EFFICACY develops a suite of approaches to sense microscopic electric fields based on time-resolved vibrational multidimensional Stark probing and excited-state symmetry breaking in tailored molecular probes. EFFICACY implements ultrabroadband femtosecond infrared (IR) light source capable of simultaneous excitation and probing of many vibrational and electronic transitions across the mid- and near-infrared spectrum. EFFICACY explores electrostatic catalytic effect in a selection of novel photoreactions using multiscale time-resolved IR spectroscopy spanning many orders of magnitude in time. Ejection of small molecules from novel classes of organic compounds and alkyne-allene photoisomerization aim to understand the through-space field effect on bond-breaking/formation and intramolecular reorganization events. The idea of alternating field chemistry is introduced, where waveform control of chemical reactivity might be a game changer to direct complex multistep processes along the desired pathway without spending any electrons.

Mots-clés : time resolved spectroscopy,ultrafast spectroscopy,multidimensional spectroscopy,infrared spectroscopy,electrostatic catalysis,reaction mechanisms,excited state symmetry breaking,electric double layer,interfaces,method development,novel photoreactions