Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : FluCoMa (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : University of Huddersfield — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1997431.0 €

The FluCoMA project instigates new musical ways of exploiting ever-growing banks of sound and gestures within the digital composition process by bringing breakthroughs of signal decomposition DSP to the toolset of techno-fluent computer composers for the first time. Cutting-edge musical composition has always been dependent on, critical and subversive of the latest advances of technology. Unfortunately, there is a contemporary challenge inherent to aesthetic research in computer composition: an ever-expanding gap between DSP advances and their availability to musical investigators. One such advance is signal decomposition: a sound can now be separated into its transient, pitched, and residual constituents. These potent algorithms are partially available in closed software, or in laboratories, but not at a suitable level of modularity within the coding environments used by the creative researchers (Max and SuperCollider) to allow groundbreaking sonic research into a rich unexploited area: the manipulation of large sound corpora. Indeed, with access to, genesis of, and storage of large sound banks now commonplace, novel ways of abstracting and manipulating them are needed to mine their inherent potential. FluCoMa proposes to tackle this issue by bridging this gap, empowering techno-fluent aesthetic researchers with a toolset for signal decomposition within their mastered software environments, in order to experiment with new sound and gesture design untapped in large corpora. The three degrees of manipulations to be explored are (1) expressive browsing and descriptor-based taxonomy, (2) remixing, component replacement, and hybridisation by concatenation, and (3) pattern recognition at component level, with interpolating and variation making potential. These novel manipulations will yield new sounds, new musical ideas, and new approaches to large corpora. At present, no library exists allowing such cutting-edge research on creative fluid corpus manipulations to be done

Mots-clés : computer composition,digital sound synthesis,creative music technology,large corpus manipulation,sound taxonomies,music information retrieval,signal decomposition dsp,creative coding environments
Projet ERC : GEODESI (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1476672.0 €

The GEODESI project aims at interpreting current and forthcoming cosmological observations in a renewed theoretical framework about cosmological inflation and its ending. The simplest toy models of inflation economically explain all current data, leaving no observational clue to guide theorists towards a finer physical understanding. In this context, I very recently unveiled an hitherto unnoticed instability at play in the primordial universe that potentially affects all inflationary models and drastically modifies the interpretation of cosmological observations in terms of fundamental physics. The so-called Geometrical Destabilization of inflation reshuffles our understanding of the origin of structures in the universe, offers a new mechanism to end inflation, and promises unrivaled constraints on high-energy physics. It is crucial to develop this fresh look before a host of high-quality data from large-scale structure surveys and cosmic microwave background observations become available within the 5 year timescale of the project. With the ERC grant I plan to build a group at the Institute of Astrophysics of Paris (IAP-CNRS) with the objective of determining the full theoretical and observational consequences of the geometrical destabilization of inflation. We will combine insights from non-standard cosmological perturbation theory and lattice simulations to constrain realistic models of inflation in high-energy physics, producing accurate theoretical predictions for a wide variety of observables, including the spectra and the non-Gaussianities of primordial fluctuations and stochastic backgrounds of gravitational waves.

Mots-clés : cosmological inflation,primordial non gaussianities,theoretical high energy physics,lattice simulations
Projet ERC : HEROIC (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Italian Institute of Technology — Pays : Italie — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1608125.0 €

The HEROIC project aims at filling the gap between the currently low operation frequencies of printed, organic flexible electronics and the high-frequency regime, by demonstrating polymer-based field-effect transistors with maximum operation frequencies of 1 GHz and complementary integrated logic circuits switching in the 10-100 MHz range, fabricated by means of printing and direct-writing scalable processes in order to retain low temperature manufacturability of cost-effective large area electronics on plastic. The recent development of semiconducting polymers with mobilities in the range of 1 to 10 cm^2/Vs, and even higher in the case of aligned films, suggests that suitably downscaled printed polymer transistors with operation frequencies in the GHz regime, at least three orders of magnitude higher than current printed polymer devices, are achievable, by addressing in a holistic approach the specific challenges set in the HEROIC trans-disciplinary research programme: (i)development of scalable high resolution processes for the patterning of functional inks, where printing will be combined with direct-writing techniques such as fs-laser machining, both in an additive and subtractive approach; (ii)development of printable nanoscale hybrid dielectrics with high specific capacitance, where low-k polymer buffer materials will be combined with solution processable high-k dielectrics, such as insulating metal oxides; (iii)improvement of the control of charge injection and transport in printed polymer and hybrid semiconductors, where high-mobility 1-D and 2-D structures are included in polymer films; (iv)development of advanced printed and direct-written transistors architectures with low parasitic capacitances for high-speed operation. HEROIC will radically advance and expand the applicability of polymer-based printed electronics, thus making it suitable for next generation portable and wearable short-range wireless communicating devices with low power consumption.

Mots-clés : printed electronics,flexible electronics,large area electronics
Projet ERC : ICE (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149720.0 €

The ICE project will demonstrate that energy regulation services can be provided to the smart grid in a technically reliable and financially lucrative fashion by utilizing a combination of smart commercial buildings and commercial batteries. The key to out-competing traditional solutions with such a service is the provision of energy storage at low capital and operational costs, which the ICE solution does via a novel hybrid storage concept that mixes the inexpensive virtual storage capacity, but slow response, of smart commercial buildings, with fast, but expensive, electrical battery systems. The ERC project BuildNet has developed advanced algorithms to manage such a hybrid system that drastically reduces the required capex-intensive battery system compared to alternative solutions. ICE will take the first step towards commercialization of this concept via a production-ready demonstration of all components of the solution, and a detailed analysis of the resulting deployment and operational costs.

Mots-clés : smart grids,smart buildings,ancillary services
Projet ERC : cureCD (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Sheba Medical Center — Pays : Israël — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

The Inflammatory Bowel Diseases (IBD), Crohn’s Disease (CD) and Ulcerative Colitis (UC) are chronic/relapsing disorders that affect over six million individuals worldwide. Mucosal ulcers, the hallmark of CD, are the result of a complex interaction between microbiota, immune cells, and gut epithelia. Healing of mucosal ulcers is associated with better outcomes, but is achieved in less than half of cases. Past attempts to suppress central and conserved nodes of the immune system failed due to opposing off-target deleterious effects on epithelial renewal. Therefore, there is a critical need to identify more tissue specific targets that lead to mucosal healing and to improved outcomes. Using mRNAseq of intestinal biopsies, we identified a widespread dysregulation of long non-coding RNAs (lncRNA) in the ileum of treatment naïve pediatric CD patients. Importently, we identified significant correlations between lncRNA and mucosal ulcers. CD lncRNA, after carful mechanistic exploration, are highly promising targets for potential future intervention as they regulate diverse cellular functions and exhibit a more tissue specific expression in comparison to protein coding genes. The core goal of this proposal is to understand the role of CD lncRNA in ulcer pathogenesis focusing on granulocytes and epithelial functions in the contexts of their interactions with the microbiota. I plan to utilize state of the art informatics, RNAseq and microbiome profiles together with advanced and novel experimental lab model and co-culture systems, patients-derived prospectively collected tissues, and gut microbiota to explore the role of CD lncRNA function in mediating healing of mucosal ulcers. This work carries the potential to guide new novel therapeutic strategies for mucosal healing with minimal off-targets effects. In a broader prospective, this work will expand our relative limited understanding regarding the role of lncRNA in mediating human diseases.

Mots-clés : crohn disease,ulcer,long non coding rna
Projet ERC : IntelliAQ (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Forschungszentrum Jülich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : FZJ
Type d'entité : Recherche
Financement ERC de l'entité : 2498761.0 €

The IntelliAQ project will develop novel approaches for the analysis and synthesis of global air quality data based on deep neural networks. The foundation of this project is the world’s largest collection of surface air quality measurements, which was recently assembled by the principal investigator and plays a pivotal role in the ongoing first comprehensive Tropospheric Ozone Assessment Report (TOAR). This database will be complemented with data from the world’s leading effort to collect global air pollutant measurements in near realtime and combined with high-resolution geodata, weather information, and satellite retrievals of atmospheric composition in order to characterize individual measurement locations and regional air pollution patterns. State-of-the-art deep learning methods will be applied to this unprecedented dataset in order to 1) fill observation gaps in space and time, 2) provide short-term forecasts of air quality, and 3) assess the quality of air pollutant information from diverse measurements. The combination of diverse data sources is unique, and the project will be the first to apply the full potential of deep neural networks on global air quality data. The achievement of the three IntelliAQ objectives will shift the analysis of global air pollutant observations to a new level and provide a basis for the future development of innovative air quality services with robust scientific underpinning. Due to the heterogeneity of the multivariate data, lack of structure, and generally unknown uncertainty of the input data, the project also poses challenges for existing deep learning methods, and will thus lead to new developments in this field. Direct outcomes of the project will be a substantial improvement of global air quality information including methods to assess the quality of air pollution measurements, and a new data-driven method for forecasting air quality at local scales.

Mots-clés : geophysical data processing,data fusion
Projet ERC : TREND (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Universidade Nova de Lisboa — Pays : Portugal — Rôle : PI
Acronyme de l'entité : NOVA
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

The Internet of Things is shaping the evolution of information society, requiring an increasing number of objects with embedded electronics, sensors and connectivity. This spurs the need for systems where summing to performance and low cost, multifunctionality has to be assured. In this context, TREND aims to take transparent electronics into as-of-yet unexplored levels of integration, by combining on flexible substrates transparent and high-speed nanocircuits with energy harvesting capabilities, all based on multicomponent metal oxide nanowires (NWs). For this end, sustainable and recyclable materials as ZnO, SnO2, TiO2 and Cu2O will be synthesized in different forms of heterostructured NWs, using low-temperature and low-cost solution processes. For precise positioning, NWs will be directly grow on flexible substrates using seed layers patterned by nanoimprint lithography. This will be crucial for integration in different nanotransistor structures, which will be combined into digital/analog nanocircuits following planar and 3D approaches. Energy will be provided by piezoelectric nanogenerators with innovative structures and materials. Final platform of nanocircuits+nanogenerators will make use of NW interconnects, bringing a new dimension to the systems-on-foil concept. The research will be carried out at FCT-UNL, in a group pioneering transparent electronics. My PhD on oxide materials/devices and proven expertise on circuit integration, oxide nanostructure synthesis and nanofabrication/characterization tools will be a decisive contribute to the implementation of the proposal. TREND is an ambitious multidisciplinary project motivating advances in materials science, engineering, physics and chemistry, with impact extending from consumer electronics to health monitoring wearable devices. By promoting new ideas for practical ends, it will contribute to place Europe in the leading position of such strategic areas, where sustainability and innovation are key factors.

Mots-clés : transparent electronics,oxide nanowires,transistors,device integration,energy harvesting
Projet ERC : LENSNOVA (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

The LENSNOVA project proposes a breakthrough both in cosmology and stellar physics, capitalising on 10 years of experience in the field of strong lensing time delays. Type Ia supernovae (SNe Ia) can now be watched on prime seats through strong lensing, where multiple images of the same SN appear at different times/locations around a foreground lens galaxy. After the first SN appears, the next SN occurrence (of the same SN event) can be predicted and observed in its entirety for the first time in history and with unprecedented temporal sampling. Observations of the beginning of SN explosions are key to revealing SN progenitors, that have been under debate for decades. Strongly lensed SNe Ia also allow an independent measurement of the Hubble constant (H0) that sets the cosmic expansion rate. The independent measurement is important to ascertain the possible need of new physics beyond the standard cosmological model, given the tensions in current H0 measurements. Capitalising on the PI’s expertise in strong lensing and success in predicting the reappearance of the first strongly lensed core-collapse SN, the objectives of LENSNOVA are to (1) place the best constraints on SNe Ia progenitors, and (2) pioneer the use of strongly lensed SNe Ia as a new cosmological probe. This will shed light on the natures of SNe Ia progenitors and dark energy, two of the greatest puzzles in the present era. The advent of the Large Synoptic Survey Telescope and the Euclid mission makes LENSNOVA particularly timely for building the first sample of ~5 strongly lensed SNe Ia. Accurate predictions of the time delays in lensed SNe Ia will allow multiwavelength observations of the reappearances of SNe, especially in the earliest days of explosion for the first time, to place the best constraints on SN progenitors. These lensed SNe Ia will also potentially yield an H0 measurement with 2% uncertainty. LENSNOVA has thus the potential to revolutionise both fields of stellar physics and cosmology.
Projet ERC : LUMIVOCS (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

The LUMIVOCS project will exploit the recently developed luminescent Guest@MOF composite materials, which exhibit unique phototunable properties to engineer a revolutionary sensor device to achieve low concentration ppm-level detection of volatile organic compounds (VOCs). Such a compact VOC sensor could be deployed for toxic VOC detection in industry and sustainability applications, or, for use in diabetes diagnostics in the healthcare and biomedical sectors. Hitherto, none of the commercial VOC sensors in the market can fulfil the requirements of high sensitivity, high selectivity, and low cost all at once. The 18-month LUMIVOCS project will de-risk the proposed technology by delivering proof-of-concept data needed to move forward towards a commercial application. To this end, the major questions that will be addressed will encompass the following areas. (i) Engineering and prototyping of a compact VOC sensor device; (ii) Evaluation of detailed sensor performance; (iii) Assessment of sensor resilience against cross contamination and photobleaching; (iv) Manufacturability, sensor lifetime and mechanical resilience. The work will be conducted in collaboration with two industrial collaborators who will provide important technical input and will lend direction to the project to facilitate commercialisation.

Mots-clés : luminescence,sensor,photonics,volatile organic compounds  voc,metal organic framework  mof
Projet ERC : TOPUP (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : University of Zurich — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UZH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2459915.0 €

The Large Hadron Collider (LHC) at CERN probes the interaction of elementary particles at unprecedented energy and to very high precision. The full exploitation of the upcoming data from the LHC relies on a close interplay between theory and experiment, which calls in particular for highly accurate theoretical predictions. This theoretical accuracy can be achieved only though the expansion of the fundamental scattering amplitudes to sufficiently high order in perturbation theory. This project aims to meet this challenge for modern collider physics by providing the conceptual and technical foundations for theory predictions at ultimate precision. TOPUP will develop and establish a new standard of theoretical precision in the description of physical observables at the LHC based on perturbation theory expanded to the third non-trivial order (N3LO). We will achieve this ambitious goal by targeting the main obstacles in present-day methods, and by developing novel ways for the computation of multi-loop scattering amplitudes and in the understanding and handling of unresolved multi-particle emission. The concrete goal of the project is to enable theoretical predictions at ultimate precision for multiple processes in high-energy particle collisions with full final state kinematical information. This will lead to a more precise extraction of fundamental physics parameters, such as couplings and particle masses. The newly developed methods will be applied to the derivation of the process-independent four-loop corrections to the Altarelli-Parisi splitting functions, the three-loop matrix elements for a number of fundamental scattering processes and fully differential N3LO predictions for several process-specific key observables. These calculations will shape and challenge the newly developed methods in cutting-edge applications and provide crucial input to the theoretical interpretation of the LHC precision physics program.

Mots-clés : collider physics,quantum chromodynamics,precision calculations,computer algebra
Projet ERC : EFT4NP (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : University of Manchester — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1407726.0 €

The Large Hadron Collider (LHC) is hunting for signs of New Physics (NP) in the vast amount of data collected by its experiments. If new states are heavier than the collider energy reach, their presence can be revealed by modifications of the interactions of the known particles. The Standard Model Effective Field Theory (SMEFT) parametrises such deviations from the SM, extending the sensitivity to scales beyond those directly probed at colliders. Determining the parameters of the EFT will shed light on the nature of NP and will provide hints to the most important questions in particle physics, such as the shape of the Higgs potential, its relation to electroweak baryogenesis and the amount of CP-violation and its connection to the matter-anti-matter asymmetry. A dedicated campaign of measurements and their SMEFT interpretation is a major goal of the LHC and requires coordination between experimentalists and theorists. I aim at making essential beyond the state-of-the-art theoretical contributions to the LHC SMEFT programme by: 1) Providing the first fully generic next-to-leading order QCD and electroweak Monte Carlo implementation of SMEFT operators, to allow theorists and experimentalists to perform realistic simulations. 2) Combining accurate SMEFT predictions with LHC data to constrain the operators through a novel robust global determination. The findings, particularly if different from the SM expectations, will point to the scale and nature of NP. 3) Exploring new challenging proposals, such as i) the impact of operator running and mixing and ii) the optimisation of ways of extracting the Higgs self-coupling and probing CP-violation at the LHC, two topics with profound implications for our theoretical understanding of particle physics. The proposal plays to a key strength of my research expertise and my research record uniquely positions me to successfully lead this ambitious project, which is vital to exploit the full LHC potential.

Mots-clés : large hadron collider,phenomenology,standard model effective field theory,new physics,precision calculations