Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet SKIN-REGEN-MECH (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : TERMINATED

Large or chronic wounds affect 4 million people in the EU each year. Tissue engineered skin substitutes offer the potential to enhance the repair and regeneration of these wounds. However, there are currently no skin substitutes that can fully restore the weight-bearing function of foot skin. Therapies to reconstruct the foot sole are urgently needed, with an increasing prevalence of diabetic foot ulcers that cost the EU €4 billion annually and have a five-year survival rate as low as 29%. Native skin’s load-bearing structure is dynamic and adaptable to changes in its mechanical environment. By studying the mechanical forces that lead to robust native skin, we can enhance regenerative therapies. The aim of this project is to enhance skin substitute design by optimising its properties using mechanobiological simulation, providing the basis for site-specific skin regeneration that targets weight-bearing function. The specific objectives of this project are: 1. To quantify cell-level mechano-regulation processes in human skin. A dynamic bioreactor will be designed to control the mechnical environment of human skin explants while the cell-level biological responses to load are quantified. 2. To optimise the mechanobiological properties of a skin substitute. A multi-scale computational model of skin mechano-regulation will be developed and used to predict the optimal mechanical and morphological properties for skin regeneration. 3. To demonstrate that this optimisation leads to enhanced dermal substitutes. The optimised skin substitute will be fabricated using bioprinting and micropatterning methods. This substitute will be tested in vitro for its ability to promote robust epidermis formation. This proposal involves substantial knowledge transfer, with the candidate gaining expertise in biomaterials and regenerative medicine, while providing the host with computational modelling and skin biology expertise. This proposal will enhance and broaden the candidate's career.

Mots clés : skin substitute, mechanobiology, surgical implant, wound healing, foot ulcers, agent based modelling, computational biology, biomechanics, mechanoregulation, in silico, in vitro, ex vivo, skin injury

Participants :
- Royal College of Surgeons in Ireland (Irlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 196590.72 €
Projet INNOVATE (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Large scale data analytics is the key research domain for future data driven applications as numerous of devices produce huge volumes of data in the form of streams. Analytics services can offer the necessary basis for building intelligent decision making mechanisms to support novel applications. Due to the huge volumes of data, analytics should be based on efficient schemes for querying large scale data partitions. Partitions contain only a piece of data and a dedicated processor manages the incoming queries. The management of continuous queries over data streams is a challenging research issue requiring intelligent methods to derive the final outcome (i.e., query response) in limited time with maximum performance. The management process of continuous queries involves their assignment to specific processors and the processing of the derived responses. We focus on a group of query controllers serving the incoming queries and, thus, becoming the connection of big data systems with the real world. INNOVATE proposes solutions for the management of the controllers behavior. We propose an intelligent decision making process for each controller in three axes: (i) top-down, by realizing a mechanism that assigns queries to the underlying processors; (ii) bottom-up, by proposing decision making mechanisms for returning responses to users/applications on top of early results; (iii) horizontal, by proposing optimization schemes for queries management. We adopt a pool of learning schemes and an ensemble learning model dealing with how and on which processors each query should be assigned. We also propose specific schemes for combining processors responses. Intelligent and optimization techniques are adopted for the controllers group management. Machine learning, Computational Intelligence and optimization are the key adopted technologies that, when combined, provide efficient solutions to a challenging problem like the support of intelligent analytics over big data streams.

Mots clés : large scale data, data streams, query streams, computational intelligence

Participants :
- University of Glasgow (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 195454.8 €
Projet SmartWood_3D (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : CLOSED

Large wood (LW) plays an important role in fluvial systems as it moderates stream power, regulates sediment transport and provides habitat for fish and other living organisms. Besides the beneficial effects of a balanced wood budget in rivers, challenges arise for abundant quantities of accessible LW. Large quantities of wood show negative effects on stream ecology, river-crossing infrastructure and flood mitigation. The sudden and disastrous occurrence of LW during floods regularly affects communities and stream systems all over the world. Due to a lack of applicable methodologies in LW research little is known about transport dynamics of wood in rivers to date. In order to expand the current understanding of flow-sediment-wood interaction processes, especially at higher flow rates, specific and profound research is required. This project aims to utilise state of the art technologies for the application in nature sciences. Nine-degree of freedom (9-DoF) smart sensors are implanted into wood logs ‘SmartWood’, to capture complex movement processes in-situ. Furthermore, Structure from Motion photogrammetry is applied for the generation of 3D LW accumulation models, on a basis of 2D images, for precise volume, porosity and surface texture evaluation. The innovative methodologies allow for novel insights into LW movement behaviour and for quantification of wood deposits, which are often obstructing and diverting the flow. An improved understanding of LW movement processes is essential to better predict arising impacts on channel morphology, river-crossing infrastructure and environment. Gained results will contribute in a more reliable risk assessment for wood prone stream systems, advanced river and forestry management strategies under consideration of LW conveyance and filtering of critical key-logs, and to realize a concept that allows wood in rivers, as a natural and environmentally important element, consistent with modern land use and infrastructure.

Mots clés : large wood  lw  research, quantification of lw movement and accumulation processes, lw jam assessment, structure from motion  sfm  photogrammetry, nine degree of freedom  9 dof  smart sensors

Participants :
- Board of the Swiss Federal Institutes of Technology (Suisse) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 191149.44 €
Projet POSEIDoN (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : CLOSED

Large-scale ocean changes, including ocean acidification (OA) and ocean warming (OW), are projected to occur over the next 50-100 years as a result of elevated atmospheric CO2. Living close to the atmosphere/ocean boundary, plankton are particularly vulnerable to, but also excellent indicators of these changes. Euthecosome pteropods (small swimming gastropods) have been highlighted as bio-indicators because their delicate aragonite shells are susceptible to OA. However complex feeding behaviours have impeded laboratory experiments on pteropods, limiting research to short term studies. The proposed action will apply an interdisciplinary approach to investigate the past, present and future effects of OA and OW upon the planktonic family Atlantidae, and to evaluate their use as bio-indicators. Atlantid heteropods are also small (max. 14 mm), aragonite shelled, planktonic gastropods that are sensitive to OA and OW. Unlike pteropods, atlantids are predatory and have the potential to be excellent experimental organisms with which to investigate the effects of these surface ocean changes. Atlantids also provide a unique opportunity to investigate the effect of OA and OW at an as-yet unstudied and potentially more sensitive trophic level. The Experienced Researcher has worked with atlantids for >8 years and is one of very few researchers able to identify atlantid species. As such, she is uniquely positioned to deliver the objectives of this interdisciplinary project. The proposed research will provide opportunities for the Researcher to advance her career and skill-set through specialist training and teaching opportunities. The proposed action will improve our appreciation of how surface ocean changes will affect zooplankton and produce high impact data that are relevant to a wide body of marine scientists. The atlantids are also beautiful, charismatic gastropods, and excellent ambassadors for engaging the public and policy makers with current ocean changes.

Mots clés : bio indicator, ocean acidification, ocean warming, pteropod, atlantidae, dna barcoding, geometric morphometrics, species boundaries, biogeography, ecological niche modelling, micropalaeontology

Participants :
- Naturalis Biodiversity Center (Pays-Bas) — Coordinator, beneficiary, Recherche, subvention : 177598.8 €
Projet PSI-FELLOW-III-3i (Horizon 2020, appel à projets 2019)
Action : Cofund Postdoctoral programme
Statut du projet : SIGNED

Large-scale research facilities are enabling cutting edge research and innovation in important domains such as materials science, health and energy. A number of such accelerator facilities is currently under construction in Europe and will become operational within the next five years. Thus, there is a growing need for highly qualified researchers trained in interdisciplinary research at such facilities and also an increasing demand from companies to use these facilities for developing and testing innovative products. The Paul Scherrer Institut (PSI), one of Europe’s leading research centres and particularly renowned for its accelerator facilities and long-standing industry collaborations, intends to establish a novel post-doctoral research programme with a broad spectrum of interdisciplinary and inter-sectoral exchange opportunities. PSI features a unique combination of excellent research facilities, including neutron, muon and light sources and (as of 2019) an X-ray free electron laser, which all exceed the possibilities of universities or industrial research centres. Motivated by the successful implementation of the H2020 COFUND programme PSI-FELLOW-II-3i, PSI now wants to further advance in post-doctoral training and education and proposes to set up PSI-FELLOW-III-3I. This 5-year programme will offer a total of 60 fellowships of two years duration each. The fellowships will be awarded in two calls for proposals with 30 fellowships in each call. In order to maximise the benefit for the Fellows and offer the widest possible range of research topics, PSI has teamed up with 46 partner organisations (34 research institutions and 12 companies). The unique setup of PSI-FELLOW-III-3i will allow using synergies with other leading research institutions for the training of the next generation of researchers specialised in tapping the full potential of large-scale research facilities, to transfer knowledge and stimulate innovation in Europe’s industries.

Mots clés : large scale facilities, matter and materials, energy and environment, human health, international, interdisciplinary, intersectoral, postdoctorand

Participants :
- Board of the Swiss Federal Institutes of Technology (Suisse) — Coordinator, beneficiary, Recherche, subvention : 4413600.0 €
Projet multiQCD (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Physics
Statut du projet : CLOSED

Lattice Quantum Chromodynamics (LQCD) is the only known systematic framework to obtain ab-initio results in the non-perturbative regime of strong interactions. Its relevance to high-energy and nuclear physics has grown significantly in recent years due in part to a series of algorithmic advancements. This project aims to compute time-like observables using numerical simulations of LQCD. Specifically, I will study spectral functions including the R-ratio, that is linked to the hadronic vacuum polarization of the electromagnetic current, and the hadronic tensor, that contains information on deep-inelastic scattering. It is extremely challenging to compute observables intrinsically defined in Minkowski spacetime with lattice techniques, with the main issue being that the simulated quantum field theory is defined in Euclidean spacetime. While Euclidean correlators contain all the information needed to extract real-time physics, performing the analytic continuation with finite-precision data points from numerical simulations is an ill-posed problem. A second issue is that the the computational cost is driven by the loss of the signal of hadronic correlators with Euclidean-time separation, that happens at an exponential rate. I will address these issues and significantly reduce the computational effort needed thanks to algorithms advancements. I plan to solve the signal-to-noise ratio problem using and further developing multi-level Monte Carlo sampling methods, that I recently contributed to extend to theories with fermions. The resulting exponential gain in the quality of the signal is essential to be able to perform the analytic continuation, that I plan to control using state-of-the-art techniques based on the Backus-Gilbert algorithm that have recently been developed by the supervisor.


Participants :
- European Organization for Nuclear Research (Suisse) — Coordinator, beneficiary, Recherche, subvention : 191149.44 €
Projet LEADERPROFILE (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : CLOSED

Leadership is a key factor for success, coherence, and progress in a multitude of compelling contexts. Not only the corporate world, the military, and politics rely on skilful leadership to bundle their potential, unite followers and members, and distil the various centrifugal forces within organisations into success. European societies currently face a climate of insecurity due to various socio-political events and, thus, perceived threat amongst citizens. Such environments have been shown to especially call for strong leadership which ensures stability and safety. However, we currently see multiple expressions of destructive leadership - i.e. a process in which the activities, experiences and/or relationships of an individual are repeatedly influenced by their supervisor in a way that is perceived as hostile and/or obstructive - around the globe, which endanger peaceful and diplomatic solutions and, thus, the success and well-being of society. Destructive, forms of leadership have barely been studied empirically, although it is known to lead to harmful behaviour, including impulsivity and aggression. Destructive leadership behaviour causes severe adverse effects amongst followers and, subsequently, hampers organisational success. It is of utmost importance to advance the theoretical understanding as well as the practical reduction of destructive leadership. To achieve this, we need to i) asses it comprehensively, ii) correctly identify sub-types, and iii) develop personalised interventions which enhance leaders’ self-reflection skills and behaviour. The proposed project will complete all three steps in the context of Executive Education. It will develop multi-dimensional assessment of destructive leadership (including self-report, follower-report, cognitive, behavioural, and biophysiological measures) and enhance existing individualised personal leadership development based on those measures, directly addressing real-world experienced leaders.

Mots clés : destructive leadership, positive leadership, narcissism, multi dimensional assessment, cognition, behaviour, bio physiology

Participants :
- Technical University of Munich (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 171460.8 €
Projet RELEARN (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Learning the statistical buildup of the environment serves the purpose of making good decisions, thus what regularities humans learn and what ones they neglect depends on the relevance towards maximizing reward. Recent studies characterise reward-based modulation of feature representations built by humans and animals both on the behavioural and neural level, but the effect of reward on learning higher-order environmental statistics is unknown. Our hypothesis is that humans do not learn to represent feature co-occurrence statistics if it does not help to predict reward due to resource constraints on computation and storage. We propose a mathematical framework based on Bayesian hierarchical modelling and reinforcement learning to predict the modulatory effect of reward on learned representations. We will test the predictions of the model in a series of experiments where humans need to learn to associate precisely controlled statistical aspects of a naturalistic simulated environment to reward both in the lab and online, in reactive and planning-based tasks. Additional to behaviour, the model will predict the structure of neural representations and their changes over the course of the experiment as well. We will test those predictions using magnetoencephalography during the learning phase of the experiments and decoding analysis to compare model variables to neural responses. The results will contribute to the understanding of representational learning in humans, with potential implications in psychiatry and economics as well as supply the community with novel analytical tools and data. The unique mentoring at the host institution together with the extensive training program including international visits to world-leading collaborators will establish my independent research program in computational neuroscience.

Mots clés : reinforcement learning, representational learning, statistical learning, bayesian brain, hierarchical perception, behavioural measurement, magnetoecephalography, neural representations

Participants :
- Max Planck Society (Allemagne) — Coordinator, beneficiary, Recherche, subvention : 174806.4 €
Projet LIMEN (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Social Sciences and Humanities
Statut du projet : SIGNED

Legal theorists have long argued that law is more than enforcement, i.e. rather than being just an externally observed phenomenon, that it involves a cognitive element on the part of participants in the practice. The dominant accounts of this cognitive element divide into those—within the law and economics paradigm—that see it as a cost-benefit analysis and others—in the natural law tradition—that conflate it with morality. Recent evidence suggests, however, that the picture is more complex: neither are human beings as relentlessly self-interested as they are parodied to be as the homo economicus of rational-choice theory nor do they possess unlimited altruism. But there has been very little systematic inquiry—certainly of an empirical nature—into the question: what are the cognitive foundations of law— as a mode of cooperation—that make it distinct from other institutions? This project will attempt to fill that gap by trying to understand the relationship between decision-making at the individual level, group behaviour and social outcomes—focusing, in particular, on the role of trust and the notion of community in mediating these relationships, and the point at which social norms “tip” into law. Joining the dots between behavioural law and economics, moral psychology, legal theory and economic sociology, it will draw on the range of methodologies currently in use in the American Empirical Legal Studies tradition (with a focus on behavioural techniques) and extend current practice by developing an approach specifically adapted to legal scholarship. This ground breaking research will seek to stretch the boundaries of current knowledge—in disciplinary, methodological and, ultimately, theoretical terms— through pioneering approaches to the empirical study of law and thereby contribute to real world change in the way that law and legal systems function, with implications for development, climate change, regional alliances and a range of other key challenges.

Mots clés : behavioural law and economics, law and norms, law and cognitive science, moral psychology, legal, theory, economic sociology

Participants :
- Stanford University (Etats-Unis) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- University of Cambridge (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 271732.8 €
Projet MEDICAL (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : CLOSED

Leprosy was an iconic disease in medieval Europe. From the 11th century, several leprosy hospitals were founded as a mitigative response to the risk of infection. Medieval treatises and chronicles suggest that leprosy was treated with medicinal plants and other ingredients of mineral and animal origin. However, very little is known about the methods used to diagnose and treat this disease within leprosaria, and medical treatments of leprosy have very rarely put in their physical context so far. Through the analysis of the dental calculus, the MEDICAL project aims to explore the medical care offered to people who experienced leprosy and lived in leprosaria in Northern Europe during the medieval period (1100-1550AD). To date, these medical treatments have never been analysed from an archaeological perspective and the study of skeletal remains recovered from selected historic leprosy cemeteries offers an unparalleled opportunity to investigate medical treatments further. The MEDICAL project will focus on two north European case studies: the cemeteries of St. Leonard at Peterborough (England) and Saint-Thomas d’Aizier (France). The research will be developed at the Department of Oral and Maxillo Facial Sciences at the Sapienza University in Rome (host institution) and at the Department of Archaeology of Durham University (secondment). Under the supervision of Professor Emanuela Cristiani (Rome) and Professor Charlotte Roberts (Durham), the applicant Dr Elena Fiorin will analyse human dental calculus employing optical microscopy, Scanning Electron Microscopy with X-ray microanalysis using Energy and Wavelength Dispersive X-ray Spectroscopy, and Inductively Coupled Plasma Mass Spectrometry. This project ultimately seeks to shed new light on the history of medieval medicine developing a novel and fresh archaeological methodology for the study of infectious diseases in the ‘golden age of bacteria’.

Mots clés : bioarchaeology, human dental calculus, medieval leprosaria, northern europe, medieval medicine, leprosy, palaeopathology, optical microscopy

Participants :
- Sapienza University of Rome (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 171473.28 €