Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet NEO (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

The genetic landscape of Europe has been extremely dynamic through time, in particular during the Neolithic transitions, and is thus difficult to redraw from the analysis of present-day populations only. Our understanding of the population migrations and cultural diffusion processes underlying the peopling of Europe has greatly advanced with recent developments in ancient DNA high-throughput sequencing. Surprisingly, despite the presence of large Neolithic human groups and its geographic location bridging Southern and Northern Europe, France is extremely under-represented in current Neolithic genomic dataset. Moreover, most recent studies focus on population migration at a global scale only, while epigenomes and oral microbiomes, which are impacted by external factors and influence the individual health and phenotype, can now be retrieved from ancient DNA sequences. NEO proposes to apply a multidisciplinary approach combining the latest advances in physical anthropology, isotopic methods, ancient genomics, metagenomics and epigenomics to two exceptional Neolithic human groups from France (Cave I of Treilles and Mont Aimé). NEO will enable us to decipher not only migration patterns and genetic ancestry, but also important aspects about life in past society, such as residential rules, funerary practices, health and diet. The success of NEO will be based on the excellent synergy between the experienced researcher and the host institution, as the applicant will benefit from state-of-the-art facilities and expertise to gain advanced training in physical anthropology methods, while applying her genomic skills to a sample set available at no other research institution in the world. By acquiring these new skills in an international context, the experienced researcher will become a fully trained evolutionary anthropo-genomicist at the interface of physical and molecular anthropology, which will place her in ideal conditions to develop as a mature and independent researcher.

Mots clés : anthropology, ancient dna, neolithic, genomics, metagenomics, epigenomics, transition, diet, funerary practices, migration

Participants :
- Université de Toulouse (France) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 185076.0 €
Projet LanguageOfDNA (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

The genomics era dawned about two decades ago with the completion of a multi-billion project sequencing the complete human genome. Today a similar task is within reach of any modestly equipped lab, due to the advances in sequencing techniques. Thousands of new species are now having their genome sequenced per year. A volume of produced genomic data challenges the interpretation capacity of classical statistical methods, opening the doors for novel machine learning approaches. A genomic sequence can be conceptually seen as a close parallel to a human language. Both utilize information (nucleotides/codons and phonemes/syllables) to encode and transmit a signal that can be faithfully decoded, with attention to error minimization, at the receiving end. Genomic messages are a product of multiple and often contradictory evolutionary pressures and are aimed to be decoded at the same time by many different actors in variable ways. For example, a genomic sequence could encode for a protein product, thus displaying a three-nucleotide / codon-based language model. However, it has also subtexts of the regulation (a codon sequence can include motifs aimed at RNA binding proteins), structural information (functional RNA folding patterns pressuring sequences to a specific direction) and so on. The main challenge of applying machine learning models to the identification of genomic function is to find creative ways to untangle these multiple layers of subtexts and focus on each type of message separately. We will adapt algorithms recently developed for the processing of human languages and use them for the classification of RNA transcripts into functional classes and the classification of untranslated functional genomic regions (enhancers, transcription factor binding sites). We will create ready-to-use datasets to benchmark existing and future methods in this field and make all DNA/RNA language models publicly available.

Mots clés : genomics, functional genomics, transcription factors, small rnas, deep neural networks, machine learning

Participants :
- Masaryk University (Rép. Tchèque) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 156980.64 €
Projet BioGeoMetal (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : CLOSED

The global oceanic oxygen content has decreased by more than 2% since 1960 and is projected to drop further in the near future. This decline could drastically impact ocean nutrient cycles and marine life, but the exact progression of ocean anoxia and its impacts are hard to predict. Earth's history is punctuated by intervals of widespread ocean anoxia that manifest themselves in the sedimentary record as specific intervals of enhanced organic-carbon burial. These intervals last for 10,000-100,000s years, are marked by perturbations to global climate and biogeochemical cycles, represent major environmental disturbances, and are often associated with mass extinctions. The study of such past climate disturbances can improve projections of future ocean anoxia and environmental change by providing better constraints on the model boundary conditions. However, this requires the detailed reconstruction of past environmental parameters based on the sedimentary record. This project aims to develop and apply new ways of using geochemical tracers for past ocean environments. The focus is on the role of trace metals in anoxic waters and their impact on marine life and biogeochemical cycles. Trace metals are essential to life and are taken up in phytoplankton cells but are also reactive towards dissolved sulphide. Though such processes leave diagnostic geochemical imprints on the isotope composition of the marine sedimentary record, their interpretation is often complicated as a result of this dual sensitivity. This research project will establish new methods to distinguish between these two controls. These methods will then be applied to samples from a variety of modern environments to establish a thorough understanding of trace metal cycling in anoxic waters. Combined with biogeochemical modelling, these new methods will then be used to reconstruct the interplay between global warming and biogeochemical cycles during an interval of widespread anoxia in the Cretaceous.

Mots clés : ocean anoxia, trace metals, nitrogen fixation, nickel, climate perturbations, cretaceous, palaeoceanography, oceanic anoxic events

Participants :
- Board of the Swiss Federal Institutes of Technology (Suisse) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 191149.44 €
Projet ReMorphOPV (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Physics
Statut du projet : CLOSED

The global transition towards clean energy requires new ways to generate electricity. One promising approach are organic bulk heterojunction (BHJ) solar cells. These devices are based on a phase-separated network of two organic materials and hold the potential to make solar power cheap and sustainable. However, there is still a lack of fundamental understanding in key areas. One important open question concerns the charge recombination. Although identified as main loss mechanism in BHJ solar cells, its underlying principles remain mysterious. ReMorphOPV comes to address these limitations by developing a new recombination model. The basic hypothesis is that a successful theoretical description must properly consider two key features of a BHJ blend: the complex nanoscale morphology and the dispersive type of charge transport. To account for both aspects, ReMorphOPV will make use of extensive kinetic Monte Carlo simulations with high spatial and temporal resolution. The proposed numerical approach includes most realistic assumptions on the nanostructure (domain size, phase purity, molecular miscibility etc.) and previously overlooked phenomena of charge transport, namely the non-equilibrium and long-range motion of carriers. The predictions of the simulations will be validated by experiments on different prototype material systems. A feedback loop between experiment and numerical model will be initialised to refine the theoretical description and define new parameterisations of the recombination rate that enable easy dissemination to other researchers. With such a model at hand, it will be possible to find design rules for organic solar cells with minimised recombination losses even at large thickness. These results are of great relevance for the photovoltaics community and will help to reinforce Europe's world-leading position in renewable energies.

Mots clés : organic photovoltaics, organic solar cells, bulk heterojunction, morphology, recombination, charge transport, numerical modelling, kinetic monte carlo method

Participants :
- Linköping University (Suède) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 80385.77 €
- Åbo Akademi University (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 93471.43 €
Projet MachineCat (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : CLOSED

The goal of MachineCat is to obtain fundamental insights into machine learning methods applied to computational chemistry problems. Machine learning methods can be used to reproduce the predictions of highly accurate electronic structure calculations at only a fraction of the original computational cost. As a consequence, it becomes possible to simulate chemical problems usually beyond the capabilities of standard computational chemistry methods. However, a routine application of machine learning methods in computational chemistry is made difficult by their inherent black box nature. MachineCat will illuminate this black box by using state-of-the-art analysis techniques to gain a deep understanding on how these learning machines operate. Based on these insights, MachineCat will then systematically improve existing machine learning methods for computational chemistry. To this end, an organocatalytic conversion reaction of carbon dioxide will be investigated. This class of reactions is highly relevant for sustainable chemistry, as it offers cheap access to value-added chemicals, potentially replacing fossil fuels as primary carbon source. By studying one particular carbon dioxide conversion reaction with machine learning methods, MachineCat will not only push the limits of these methods, but also provide a detailed mechanism for the reaction under study for the first time. MachineCat will then use this information to rationally design improved catalysts for the conversion reaction. The researcher will gain expertise in modern machine techniques and transfer expertise in computational chemistry to the host. The networks of researcher and host will profit from two interdisciplinary workshops. MachineCat will prepare the researcher for an independent career, providing him with a unique research profile, excellent teaching and presentation skills, strong management capabilities, extensive experience in public engagement and dissemination, and a wide scientific network.

Mots clés : machine learning, organocatalysis, carbon fixation, quantum chemistry, catalyst design, carbon dioxide activation

Participants :
- Technische Universität Berlin (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 159460.8 €
Projet LiquidEff (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

The goal of the LiquidEff project is to significantly advance the state of the art of type-based reasoning about the correctness of programs that can incorporate computational effects such as accessing memory, raising and handling exceptions, making nondeterministic and probabilistic choices, and communicating over a network---all integral features of modern mainstream programming languages. The timeliness and importance of this project is demonstrated by the staggering cost of software failure in our increasingly digital world---one recent study put the number at $1.7 trillion worldwide in 2017 alone. While there already exist different approaches to type-based reasoning about the correctness of effectful programs, they all have their notable shortcomings: the approaches might be tied to a specific typing discipline, the supported effects can be limited, and the kind of properties one can reason about may be restricted. In contrast, the LiquidEff project aims to develop a foundational, uniform, and widely applicable framework for type-based reasoning about effectful programs, based on the highly scalable and modular algebraic approach to modelling computational effects. Specifically, this project will 1) develop an expressive modal logic for reasoning about a wide range of computational effects; 2) show that this logic can express existing effect specification styles; 3) demonstrate that it can be used to design refinement type systems for lightweight type-based reasoning about effectful behaviour, thus giving a general account of the Liquid Effects effect-typing discipline that so far has been restricted to the state effect; 4) study the category-theoretic semantics of these foundations; 5) implement LiquidEff, an extension of the Eff language with a support for lightweight type-level reasoning about programs' behaviour; and 6) use LiquidEff to apply the developed theory in practice to case studies involving big data and asynchronous parallel programming.

Mots clés : algebraic effects, effect handlers, refinement types, liquid types, liquid effects, algorithmic typechecking, denotational semantics, fibrations, monads, adjunctions, algebraic theories

Participants :
- University of Ljubljana (Slovénie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 150040.32 €
Projet MCT (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Mathematics
Statut du projet : CLOSED

The goal of the project is to advance our understanding of the central questions in Computational Complexity Theory such as the famous P versus NP problem. Complexity Theory approaches questions about efficiency of computation by investigating lower and upper bounds on the complexity of concrete computational models such as Boolean circuits or propositional proof systems. Unfortunately, even after several decades of intense research the progress on the question of proving strong complexity lower bounds remains very incremental. In fact, several significant barrier results have been discovered, partially explaining the complexity of establishing complexity lower bounds. While the barrier results presented a serious obstacle they also revealed new structural properties of complexity lower bounds connecting lower bounds to the construction of efficient learning algorithms, cryptography or independence results in mathematical logic. The present project continues the development of these structural connections and complexity-theoretic properties of problems about complexity, which we shortly refer to as Metacomputational Complexity Theory. The objectives of the project can be divided into two groups. 1. Hardness magnification, exploring limits and consequences of an emerging theory of hardness magnification which arouse recently from investigations of metacomputational aspects of circuit lower bounds and received a lot of attention as a promising approach overcoming previously existing barriers for proving complexity lower bounds. 2. Structural theory, strengthening and generalizing connections between the methods for proving lower bounds and other central concepts of computer science, such as efficient learning algorithms, cryptographic primitives and automatizability of propositional proof systems, through the lens of mathematical logic.

Mots clés : computational complexity, circuit complexity, mathematical logic, proof complexity

Participants :
- University of Oxford (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 212933.76 €
Projet HELPS (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Physics
Statut du projet : CLOSED

The goal of this project is the development of a novel, hybrid and scalable quantum photonic circuit that enable the generation of tunable, brightness and indistinguishable single photons on-demand by the deterministically integration of III-V quantum emitters coupled to a planar hyperbolic metamaterial (HMM) resonator-antenna. The implementation of the multilayered HMM over the semiconductor quantum dots (QDs) will be carry out by Micro/Nano Litography. The innovative design of this proposal will enable to ensure the coupling between the emitter and far-field radiation channels and will provide extremely high Purcell factor and brightness enhancement. While single emitters coupled to plasmonic waveguides have been widely studied, there are no experiments with HMM Resonator-Antenna in the literature, even when it is proved that is compatible with a wide variety of sources and capable of room temperature operation due to the broad bandwidth enhancement of spontaneous emission and directional photon emission. Finally, HELPS project will contribute to the understanding of the novel applications and functionalities of HMM coupled to semiconductors nanomaterials.

Mots clés : metamaterials, quantum photonics, micro spectroscopy, single photon

Participants :
- Tampere University (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 202680.96 €
Projet EXPMFSG (Horizon 2020, appel à projets 2014)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Physics
Statut du projet : CLOSED

The goal of this project is to contribute to the design and execution of a precise experimental test of a theory for the glass and jamming transitions. Indeed, the last few years have witnessed a considerable advance in the microscopic description of glassy systems: an intrinsic relation between these two transitions has been uncovered. The phase diagram was obtained, finding that the jamming transition is located inside the glass phase and corresponds to a transition from entropic rigidity to mechanical rigidity. This last year has brought new breakthroughs: the jamming critical exponents can be computed with the theory, which suggests a precise test in a lab. The testing of these new progresses in theory requires an integrated research program joining theory and experiment, an opportunity that is emerging in Paris, by the collaboration of the group of F. Zamponi (supervisor of this action and one of the co-authors of the main last theoretical results) with the nearby experimental group leaded by O. Dauchot. Hereby, I present this project with the aim of being part of this exciting opportunity.

Mots clés : glass transition, jamming transition

Participants :
- Centre national de la recherche scientifique (France) — Coordinator, beneficiary, Recherche, subvention : 173076.0 €
Projet PROCESS REASONING (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : CLOSED

The goal of this project is to develop a formal framework for reasoning about processes, as a contribution to modal-temporal logic, process ontology, formal semantics, and AI. The core metaphysical idea is this: the world is constantly changing – it is full of happenings and doings –, and the future is open. Even though this idea meshes very well with our common-sense reasoning about the world, an entirely static – pointillistic – picture of reality has established itself as the standard theoretical account. On that picture, the world is but a sequence of static states, and change is nothing over and above an object having different properties at different times. While the static idea fits well with our mathematical description of the world, it does not square with our intuitions about time, change, and agency. The last decades have thus witnessed a growing interest in a dynamic world view, and theories building on genuine dynamic entities, such as processes, dispositions, or powers, are on the rise. Despite the increasing interest in a dynamic conception of reality, the formal foundations of such views are notoriously under-investigated. The present project aims to fill in this lacuna: building on previous work by the ER, the project will propose a formal account of processes as genuinely dynamic entities and implement that account in a branching time logic. In developing a dynamic account of processes and their modal-temporal properties, the project will draw on discussions in the metaphysics of time and modality in order to arrive at a formal framework that is philosophically well-informed. Vice versa, making the ideas formally precise will help to clarify fundamental metaphysical questions. But the prospects of the project go far beyond philosophy: a rigorous formal account of processes will also prove fruitful in the study of tense and aspect in linguistics, and it opens up the possibility for implementation in AI and social robotics.

Mots clés : modal temporal logic, process ontology, philosophy of time and modality

Participants :
- Aarhus University (Danemark) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 207312.0 €