Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DiaDev (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : Heriot-Watt University — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 23500.31 €

Many people living in resource-poor settings have never had access to the laboratory facilities or technical expertise that are needed to diagnose diseases. With the development and deployment of a new generation of affordable, easy-to-use, and portable diagnostic devices that are designed for places with no laboratory infrastructure, the global landscape of diagnosis is dramatically changing. Can portable diagnostic devices strengthen health systems in resource-poor settings? DiaDev is the first study to comprehensively address this question through comparison across multiple devices, sites of production, and contexts of use. Diagnostic technologies are often championed as universal solutions to health equity and access. This ethnographic study investigates the extent to which how diagnostic devices work and what they can achieve depends on the locally specific relationships through which they are designed and used. Five ethnographic case studies from the USA, India and Sierra Leone examine the partnerships between donors, governments, humanitarian organisations and users that characterise current models of technological innovation and implementation in global health, the processes by which diagnostic devices are integrated with health infrastructures in target settings, and the practices of knowledge production and use they entail. The ultimate aim is to generate new insight into (i) changing relationships of power between governments, donors, and business in global health, and (ii) the ways in which diagnostic devices are transforming health systems in resource-poor settings. It will produce a new context-specific and comparative framework for exploring the opportunities and challenges involved in the design and use of diagnostic devices. Through innovative collaborative methods it will also develop a set of ‘health system strengthening tools’ that will enable stakeholders to improve the design and use of these devices in dialogue with the project findings.

Mots-clés : global health,institutions,partnership,value,humanitarian enterprise
Projet ERC : SAFEBIO (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Helsinki — Pays : Finlande — Rôle : PI
Acronyme de l'entité : UH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498367.0 €

Many real-world problems are modeled as computational problems, but unfortunately with incomplete data or knowledge. As such, they may admit a large number of solutions, and we have no way of finding the correct one. This issue is sometimes addressed by outputting all solutions, which is infeasible for many practical problems. We aim to construct a general methodology for finding the set of all sub-solutions common to all solutions. We can ultimately trust these to be part of the correct solution. We call this set "safe". Ultimately, we aim at creating automated and efficient ways of reporting all safe sub-solutions of a problem. The main motivation of this project comes from Bioinformatics, in particular from the analysis of high-throughput sequencing (HTS) of DNA. One of the main applications of HTS data is to assemble it back into the original DNA sequence. This genome assembly problem admits many solutions, and current research has indeed considered outputting only partial solutions that are likely to be present in the correct original DNA sequence. However, this problem has been approached only from an experimental point of view, with no definite answer on what are all the safe sub-solutions to report. In fact, the issue of safe sub-solutions has been mostly overlooked in Bioinformatics and Computer Science in general. This project will derive the first safe algorithms for a number of fundamental problems about walks in graphs, network flows, dynamic programming. We will apply these inside practical tools for genome assembly, RNA assembly and pan-genome analysis. This is very relevant at the moment, because HTS goes from research labs to hospitals, and we need answers that are first of all accurate. Our approach changes the perspective from which we address all real-world problems, and could spur a new line of research in Computer Science/Bioinformatics. The grand aim is a mathematical leap into understanding what can be safely reported from the data.

Mots-clés : genome assembly,rna transcripts,pan genomes,edit distance,variant calling,graph algorithms,walks,network flows,shortest paths,bipartite matching,dynamic programming
Projet ERC : GUPPYCon (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : University of Sussex — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 152180.37 €

Many species have independently evolved similar phenotypes in response to similar environmental challenges. This phenomenon, termed convergent evolution, reflects both the power and the limits of adaptation. However, we often do not know at what scale evolution has repeated itself: did selection act on the same genes in different populations or species, or did convergence result from selection on different genes? This is because, until recently, it has not been possible to investigate the genomic basis of evolution in most systems, limiting our understanding of the factors that facilitate or inhibit convergence and adaptation. To fully understand convergent evolution we need to query the genomic response to selection and determine genotype-phenotype links in systems where convergent adaptation is well established. The Trinidadian guppy (Poecilia reticulata) is a system that offers the opportunity to test the roles of multiple factors in convergent evolution: this species includes multiple natural and experimentally established populations that have repeatedly evolved similar phenotypes under similar predation environments. I propose to fully characterize the genomic-basis of repeated adaptive evolution in guppies. Aim 1 will identify regions that repeatedly show signatures of selection, and will contrast the nature of selection in natural and experimental populations that differ in age and levels of founding genetic diversity. Aim 2 will identify genomic regions associated with phenotypes that are known to play a significant role in local adaptation in the guppy using quantitative genetics approaches. I will then directly test the effects of candidate genes using novel functional genomic approaches, as detailed in Aim 3. Overall, this project will test whether repeated selection led to convergence at the genomic level, determine the genetic basis of convergent adaptations, and ultimately understand how convergent evolution has occurred in an important wild system.

Mots-clés : evolution,adaptation,population genomics,quantitative genetics
Projet ERC : NICHOID (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Politecnico di Milano — Pays : Italie — Rôle : PI
Acronyme de l'entité : POLIMI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1802830.0 €

Many therapeutic applications of stem cells require accurate control of their differentiation. To this purpose there is a major ongoing effort in the development of advanced culture substrates to be used as “synthetic niches” for the cells, mimicking the native ones. The goal of this project is to use a synthetic niche cell culture model to test my revolutionary hypothesis that in stem cell differentiation, nuclear import of gene-regulating transcription factors is controlled by the stretch of the nuclear pore complexes. If verified, this idea could lead to a breakthrough in biomimetic approaches to engineering stem cell differentiation. I investigate this question specifically in mesenchymal stem cells (MSC), because they are adherent and highly mechano-sensitive to architectural cues of the microenvironment. To verify my hypothesis I will use a combined experimental-computational model of mechanotransduction. I will a) scale-up an existing three-dimensional synthetic niche culture substrate, fabricated by two-photon laser polymerization, b) characterize the effect of tridimensionality on the differentiation fate of MSC cultured in the niches, c) develop a multiphysics/multiscale computational model of nuclear import of transcription factors within differentially-spread cultured cells, and d) integrate the numerical predictions with experimentally-measured import of fluorescently-labelled transcription factors. This project requires the synergic combination of several advanced bioengineering technologies, including micro/nano fabrication and biomimetics. The use of two-photon laser polymerization for controlling the geometry of the synthetic cell niches is very innovative and will highly impact the fields of bioengineering and biomaterial technology. A successful outcome will lead to a deeper understanding of bioengineering methods to direct stem cell fate and have therefore a significant impact in tissue repair technologies and regenerative medicine.

Mots-clés : mechanobiology,multiphysics,multiscale,mesenchymal,stem cell,differentiation,microfabrication,two photon polymerization,synthetic niche,substrate,cell culture
Projet ERC : SIAM (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Hebrew University of Jerusalem — Pays : Israël — Rôle : PI
Acronyme de l'entité : HUJI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1373057.0 €

Many world-changing breakthroughs in science and technology were enabled by analogical transfer, as ideas from one domain were used to solve a problem in another. Observing water led the Greek philosopher Chrysippus to speculate that sound was a wave phenomenon; an analogy to twisting a cardboard box allowed the Wright brothers to design a steerable aircraft. Despite its value for innovation, very little progress has been made towards automating the process of analogy-finding in real-world settings, and the problem has maintained a longstanding status as a "holy grail" in artificial intelligence (AI). The goal of this proposal is to tackle head-on this important problem and develop principled tools for automatically discovering analogies in large, unstructured, natural-language datasets such as patents and scientific papers. Such tools could revolutionize a variety of fields, allowing scientists and inventors to retrieve useful content based on deep structural similarity rather than simple keywords. The explosion of data available online, coupled with novel machine learning and crowdsourcing techniques, creates an unprecedented opportunity to develop novel methods to accelerate innovation and discovery. My approach explores the multiple roles AI and machine learning can play in the analogical innovation pipeline. This research will focus on the three core components of the pipeline -- (1) developing representations and similarity metrics to facilitate comparison between potential analogs, (2) imbuing the algorithms with commonsense knowledge and abstraction capabilities, and (3) guiding the adaptation of the discovered analogies to solve the original problem. For each component, the proposal demonstrates how recent advances suggest effective approaches, and describes our concrete preliminary results and ideas to serve as starting points and indicate the feasibility of this challenging project.

Mots-clés : analogy,innovation,data mining,text mining
Projet ERC : MapCOM (Horizon 2020, appel 2015, Proof of concept grants)
Entité participante : Chalmers University of Technology — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 66250.0 €

MapCOM will transition the fundamental research carried out in the COOPNET project (the PI’s Starting Grant Project) to concrete applications related to power-efficient and scalable resource allocation for cellular networks, in particular for 5G communications. The key idea is to harness uncertain location information to build statistical radio maps, which can be used to predict radio signal quality and perform long-term proactive resource allocation. This will reduce operating costs for operators, provide better user experience for high-throughput applications, and enable new services and applications where low latency, reliable, and scalable communication is key (e.g., autonomous vehicles). Our COOPNET research has indicated the importance of explicitly accounting for various sources of uncertainty. We are now ready to establish the innovation potential of this research for commercial and societal benefit. Funded by the Western Sweden Innovation Office, we have already taken initial steps in this direction and have established possible innovation potential through meetings with Ericsson and Alcatel-Lucent, two equipment manufacturers. In this ERC Proof of Concept, we plan to demonstrate the technology and determine the market potential by: (i) confirming that the performance gains seen in theory also hold up in the real world; (ii) identifying possible market applications starting with telecom equipment manufacturers and telecom operators, but also other ICT industries. This analysis will allow us to identify, together with industrial actors, where the market value of the COOPNET concept lies. If successful, telecom equipment manufacturers and/or telecom operators will be able to provide the COOPNET functionality as part of their future products and services, giving them a significant advantage over competitors. We also expect this to be a first step towards multiple possible market applications to be identified in various areas of the ICT industries.

Mots-clés : 5g communication,crowd sourcing,radio mapping,network optimization
Projet ERC : MYCO-CARB (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Marine Biological Association of the United Kingdom — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : MBA
Type d'entité : Recherche
Financement ERC de l'entité : 1960141.0 €

Marine planktonic fungi (mycoplankton) have been largely ignored compared to other plankton groups, such as phytoplankton, especially the roles that they fulfil in marine ecosystems. My research has shown that mycoplankton are a major structural and functional component of coastal ecosystems that have been almost completely overlooked. I have shown that mycoplankton are a substantial proportion of plankton biomass and that saprotrophic mycoplankton are active in coastal ecosystems. Mycoplankton are also a major plankton group in the open ocean and dominate on marine snow particles. These studies demonstrate that fungi have potential roles in the marine carbon cycle including the biological carbon pump. The absence of fungi within a general view of the structure and function of the marine carbon cycle, including a lack of mechanistic understanding of saprotroph functional biology and ecology, represent major knowledge gaps in our understanding of marine ecosystems that must urgently be addressed. MYCO-CARB will address these knowledge gaps through an innovative programme of research. Research cruises at established marine observatories will make an unprecedented assessment of active mycoplankton diversity and abundance across a range of ecosystems; from surface coastal waters to the deep open ocean. Innovative approaches, including molecular ecology tools and ecosystem modelling, will establish the impact of fungal saprotrophs on the marine carbon cycle. A culture collection will be developed, informed by the field-based surveys of natural assemblages to produce ecologically-relevant model fungi. Complementary culture-dependent and -independent systems biology methodologies will determine the underpinning biological machinery of saprotrophic marine mycoplankton. Through the MYCO-CARB research programme, I will open the marine fungal ‘black box’, revealing marine mycoplankton functional biology and ecology, and establishing their roles in the marine carbon cycle.

Mots-clés : marine microbial ecology,fungal ecology
Projet ERC : IsoMS (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Charles University — Pays : Rép. Tchèque — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 429730.44 €

Mass spectrometry (MS) in combination with electrospray ionization (ESI) is one of the principal tools currently used to gain insight into newly developed catalytic reactions. It is used to identify key reaction intermediates and to study their structure and reactivity. This proposal is based on the combination of modern MS approaches with novel experiments in a unique cryo-trapping instrument. This combination allows the study of short-lived ionic species that cannot be studied by other known methods. Our distinguishing feature is the in situ helium-tagging of ions, which allows us to record their infrared spectra via a pre-dissociation technique. Here, we will go beyond this state-of-the-art approach in two directions: (1) The unparalleled advantage of ESI-MS is its high sensitivity to low-abundant and reactive species. The pertinent question at the heart of all reaction mechanism investigations via MS is how the ions found in the gas-phase relate to the condensed-phase reaction. We will address this question using “Delayed Reactant Labelling”, which will directly link condensed phase kinetics to the abundance of isolated gaseous ions. (2) We will take advantage of long storage times in our cryogenic linear quadrupole trap and expand the portfolio of the methods available to address mixtures of ions with the same mass. Isobaric mixtures are resolved in MS by differences in ion mobilities, i.e. the ions are separated by their mass-to-charge ratios and by their shapes. We will perform ion mobility separation directly in the trap by excitation of the ion secular motion using a resonant dipolar electric field. Further, we will combine cryo-trapping experiments with the probing or modifying of the stored ions by reactive collisions with neutral molecules. The mobility experiments and the reactivity probing will be routinely combined with spectroscopic experiments.

Mots-clés : ion chemistry,reaction intermediates,low temperature experiments
Projet ERC : ADAM (Horizon 2020, appel 2019, Synergy grants)
Entité participante : University of Rostock — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2387148.0 €

Materials impact most aspects of our lives, including healthcare, energy production, data storage and pollution control. However, the design of functional materials cannot be approached with the certainty and the engineering rules that would be used in planning and constructing a macroscopic object, such as a car or bridge. This is because of the limited scope for design that exists at the atomic scale: experimentally realizable materials must correspond to local minima on a complex, multidimensional energy surface, whose positions and depths are difficult to predict. This project will change the way that we discover new molecular materials by revolutionizing the exploration process, rather than focussing on rules for intuitive design. This will be achieved through a unique synergistic partnership between three principal investigators, bringing together an international leader in crystal structure modelling and prediction methods, an experimental chemist with a track record for inventing new classes of functional materials, and a pioneer in robotics for laboratory and process automation. The programme integrates state-of-the-art computation, experiment and robotics, building on joint breakthroughs from our team (Nature, 2011; Nature, 2017) that lay the groundwork for a transformation in our materials discovery capabilities. We will build a Computational Engine for evolutionary exploration of chemical space using crystal structure prediction and machine learning of structure-property relationships for the assessment of molecules. In parallel, we will develop an Experimental Engine for autonomous synthesis and properties testing using newly-developed, artificially-intelligent, mobile ‘robot chemists’. The vision of ADAM is to couple these two engines together, creating an autonomous discovery platform that amplifies human creativity by searching the vast, unexplored chemical space for new materials with step change properties.

Mots-clés : materials discovery,chemistry automation
Projet ERC : WoodNanoTech (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : KTH Royal Institute of Technology — Pays : Suède — Rôle : PI
Acronyme de l'entité : KTH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2461947.0 €

Materials tend to be either structural or functional. Here focus is on biobased composites combining both aspects, using nanostructured wood templates. Wood is the most widely used biobased material for load-bearing structures, but the range of achievable properties and functions can still be increased. The objective is to develop scalable nanotechnology for wood structures, utilizing its nanocellulosic skeleton. Processing and materials design concepts are developed in the form of a wood nanotechnology toolbox. Focus is on transparent wood for engineering applications, a concept pioneered in my laboratory. Transparent wood can combine load-bearing properties with photonics functions and light weight. The cellulose nanofibril skeleton in wood is a sophisticated reinforcement structure. For transparent wood, processing to nanoporous but mechanically robust templates without chromophores, is needed. Templates are then further functionalized using in-situ polymerization and/or inorganic nanoparticle precipitation. Molecular dynamics simulations are used to design polymers and methods for cellulose surface modification. Optical property research on material effects on scattering, polarization properties will then generate new ideas in "wood photonics". Device functions can be integrated in large structures, using anisotropy and the hierarchical structure in wood. Optically functional additives can be used to generate unique effects for applications such as lighting systems, LED panels, wood lasers, electrochromic windows or load-bearing and transparent panels with tailored combinations of transmittance and haze. Optical and mechanical properties are studied using experiments and modeling. The project team combines polymeric biocomposites competence with photonics expertise in a multidisciplinary effort.

Mots-clés : nanostructured biocomposites,materials design,processing concepts