Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ASYMOW (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Scuola Normale Superiore — Pays : Italie — Rôle : Partner
Acronyme de l'entité : SNS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 312500.0 €

Despite its success in describing the sub-nuclear realm, the Standard Model of particle and field interactions cannot account for a number of experimental facts that constitute evidence of new and unknown physics. Sitting at both the energy and intensity frontier, the LHC grants the highest chances for solving the current puzzle. By exploiting the data collected by the CMS experiment at the LHC, ASYMOW aims at attaining an unprecedented experimental accuracy on a fundamental parameter of Nature: the mass of the W boson. As of today, there is a tension between the Standard Model expectation and the measured value of the W boson mass. A new measurement with a 10 MeV uncertainty, i.e. twice as small as the single best measurement, is a breakthrough: it could either rule out the tension or build a convincing case that this anomaly is real, thus implying the existence of new physics. The collider physics community has been pursuing this goal for decades. The quest now seems to have hit the wall of systematic uncertainty. This project proposes a new approach towards the W boson mass measurement, which will circumvent the systematic uncertainties that are currently limiting the precision. The novelty of the proposed method lies in its agnosticism with respect to the microscopic picture of W boson production in hadron collisions. The loss of prior knowledge inherent to this new approach will be asymptotically compensated by the large amount of data available for the measurement, as will be collected at the LHC. ASYMOW will be conducted by a small group of scientists and comes with great experimental and theoretical challenges. The main expected result is the measurement of the W boson mass with a precision better than the state-of-the-art. This may open new scenarios in particle physics.

Mots-clés : w mass,precision electroweak measurements,standard model
Projet ERC : ATMEN (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Vienna — Pays : Autriche — Rôle : PI
Acronyme de l'entité : Univie
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1497202.0 €

Despite more than fifty years of scientific progress since Richard Feynman's 1959 vision for nanotechnology, there is only one way to manipulate individual atoms in materials: scanning tunneling microscopy. Since the late 1980s, its atomically sharp tip has been used to move atoms over clean metal surfaces held at cryogenic temperatures. Scanning transmission electron microscopy, on the other hand, has been able to resolve atoms only more recently by focusing the electron beam with sub-atomic precision. This is especially useful in the two-dimensional form of hexagonally bonded carbon called graphene, which has superb electronic and mechanical properties. Several ways to further engineer those have been proposed, including by doping the structure with substitutional heteroatoms such as boron, nitrogen, phosphorus and silicon. My recent discovery that the scattering of the energetic imaging electrons can cause a silicon impurity to move through the graphene lattice has revealed a potential for atomically precise manipulation using the Ångström-sized electron probe. To develop this into a practical technique, improvements in the description of beam-induced displacements, advances in heteroatom implantation, and a concerted effort towards the automation of manipulations are required. My project tackles these in a multidisciplinary effort combining innovative computational techniques with pioneering experiments in an instrument where a low-energy ion implantation chamber is directly connected to an advanced electron microscope. To demonstrate the power of the method, I will prototype an atomic memory with an unprecedented memory density, and create heteroatom quantum corrals optimized for their plasmonic properties. The capability for atom-scale engineering of covalent materials opens a new vista for nanotechnology, pushing back the boundaries of the possible and allowing a plethora of materials science questions to be studied at the ultimate level of control.

Mots-clés : graphene,scanning transmission electron microscopy,first principles modeling
Projet ERC : OUTSOURCE (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Oslo University Hospital — Pays : Norvège — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1020437.5 €

Despite recent advances in cancer immunotherapy, most patients with metastatic cancer are not cured. Major reasons are lack of homogeneously and highly expressed molecules that can be safely targeted and evoke efficient T-cell responses. I propose that the strong T-cell responses leading to rejection of transplanted organs can be exploited to “reject” cancer by specific recognition of tissue-restricted targets. To this end, I recently demonstrated that healthy donor blood provides a rich source of T cells expressing TCRs that specifically and strongly react to peptides from tissue-restricted self-proteins, when presented on mismatched, foreign Human Leukocyte Antigens (HLA). I propose that patient T cells genetically equipped with such donor TCRs (dTCR T cell therapy) may “reject” cancer-affected organs, including metastases. A high and homogeneous expression of tissue-specific antigens is often maintained on both primary tumor and metastatic cancer cells. Here, I will identify peptides from tissue-restricted proteins as novel candidate TCR targets. Next, I will identify donor T cells that recognize such self-peptides in complex with foreign HLA by use of my patented method, and sequence reactive TCRs. Finally, I will establish a preclinical pipeline to characterize safety and efficacy of TCRs in vitro and in vivo in innovative mouse models. Outsourcing cancer immunity to dTCR T cells may bypass major limitations in current immunotherapies, including checkpoint inhibition and T cells gene-modified with chimeric antigen receptors (CARs). Thus, dTCRs can recognize i) intracellular targets and thus manifold more targets than CARs, ii) tumor-associated self-antigens with high affinity in contrast to patient-derived TCRs, and iii) self-antigens, which are more homogeneously expressed than mutations. dTCR T cell therapy could treat malignancies in organs that are non-essential for survival, such as prostate, or that can be replaced by a transplant, such as bone marrow.

Mots-clés : cancer immunotherapy  adoptive t cell therapy  t cell receptor engineered t cells
Projet ERC : NatDyReL (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : German Aerospace Center — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : DLR
Type d'entité : Recherche
Financement ERC de l'entité : 1567702.54 €

Despite the significant progress made in the field of humanoid robotics over the last 10-15 years, bipedal locomotion in robotics is still far from human performance in terms of speed, versatility, and robustness. The design of most humanoid robots nowadays is dominated by the aim at high rigidity and position accuracy in the motor units. In contrast, the NatDyReL project aims at a fundamental shift of paradigm in the design and control of humanoid robots, towards a new generation of intrinsically compliant robots that can adjust their open loop actuator impedance in real-time to the task. We believe that the maturing technology of variable impedance actuators in combination with novel control approaches for the intrinsically elastic dynamics has the potential of bringing humanoid locomotion and multi-contact motions to a new level in terms of energy-efficiency and execution speeds more similar to the human archetype. However, to fully utilize the ultimate benefits promised by variable impedance actuators, i.e. to store and release energy as well as to provide physical protection against shocks caused by impacts, it is necessary to exploit the natural compliant whole body dynamics on all levels of the system design, planning and control hierarchies. This project follows two scientific tracks for achieving (a) energetically efficient and high performant legged locomotion and (b) robust and dynamic contact transitions and in-contact motions for whole body locomotion in uncertain and confined spaces. As a strong basis to the mentioned application oriented objectives, we also aim at fundamental contributions on the control challenges related to novel variable impedance actuator technologies. The project is expected to make a strong impact on bipedal humanoid locomotion. Moreover, the developed methods will be sufficiently general such that they can also be transferred to other morphologies such as e.g. multi-limbed walking or climbing robots.

Mots-clés : humanoid robots,locomotion,walking machines,natural dynamics
Projet ERC : DYNAMOF (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : University of Vienna — Pays : Autriche — Rôle : PI
Acronyme de l'entité : Univie
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1964345.0 €

Despite the staggering number of reports on Metal-Organic Frameworks (MOFs), we are still greatly limited in our ability to manipulate colloidal MOF particles and control MOF orientation. Reliable control of MOF crystal orientation is extremely important as the properties and functionality of most MOFs are highly dependent upon crystallographic direction due to lattice anisotropy. However, the effective exploitation of such functionality remains frustratingly out of reach. Based on the novel concept of exploiting MOF anisotropic ion mobility and polarizability, DYNAMOF aims to establish a flexible toolbox of methods for both dynamic and static control over the orientation, alignment and deposition of MOF crystals, which can be integrated into other processing techniques, thus paving the way for major advancements in the performance of MOF materials, composites and devices. The mechanisms of E-field alignment of MOF particles as well as colloidal interactions governing MOF plastic or liquid crystal assembly, non-classical crystal growth and oriented film formation will be studied to develop a comprehensive and revolutionary platform for orientational control of free-standing and supported MOF crystals. As a proof-of-concept, the implications of MOF alignment on the proton conduction of MOF composites will be tested to pave the way towards next-generation MOF proton exchange membranes. This ambitious project, which straddles the disciplines of materials science, chemistry and physics, is expected to break new ground by removing a key barrier in our ability to manipulate MOF particles. The wider goal of DYNAMOF is to establish the principles and working methods for colloidal manipulation across a wide materials spectrum, by using MOFs as a versatile platform for expanding our understanding of colloidal materials. Given the ubiquity and importance of colloids in materials science and daily life, the success of DYNAMOF will therefore have far reaching impact.

Mots-clés : colloidal assembly,liquid crystals,electrophoretic deposition,metal organic frameworks,proton conductivity
Projet ERC : BRISC (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Ulm — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1434250.0 €

Despite their many successes and great computational power and speed, why are machines still so blatantly outperformed by humans in uncertain environments that require flexible sensorimotor behavior like playing football or navigating a disaster zone? Answering this question requires understanding the mathematical principles of biological sensorimotor control and learning. Over the recent years Bayes-optimal actor models have widely become the gold standard in the mathematical understanding of sensorimotor processing in well-controlled laboratory tasks. However, these models quickly become intractable for real-world problems because they ignore the computational effort required to search for the Bayes-optimum. What is therefore needed is a framework of sensorimotor processing that takes the limited information-processing capacity of bounded rational actors into account and that explains their robust real-world performance. It is the aim of BRISC to establish such a framework by drawing out theoretical predictions and gathering experimental evidence in human motor control, in particular to understand (i) how single bounded rational actors deviate from Bayes-optimal behavior in motor tasks, (ii) how multiple bounded rational actors organize themselves to solve motor tasks that no individual can solve by themselves and (iii) how this drives the emergence of hierarchical control structures that simultaneously process multiple degrees of abstraction at different time scales. Understanding how abstract concepts are formed autonomously from the sensorimotor stream based on resource allocation principles will establish an essential missing link between high-level symbolic and low-level perceptual processing. These advances will provide a decisive step towards a framework for robust and flexible sensorimotor processing, which is not only essential for understanding the fundamental principles of intelligent behavior, but it is also of potentially great technological value.

Mots-clés : motor control,decision making,sensorimotor learning,biological information processing,computational modeling,cognitive modeling
Projet ERC : STATLEARN (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Scuola Internazionale Superiore di Studi Avanzati — Pays : Italie — Rôle : PI
Acronyme de l'entité : SISSA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1498210.0 €

Despite written language is not part of our genetic endowment, literate adults process an impressive amount of information as they read, and do that extremely flawlessly and nearly error-free. How this happens is largely unknown, and represents a fundamental issue for theories of human learning. Building on data from nonhuman primates, human infants and psycholinguistic experiments on word internal structure, STATLEARN tests the hypothesis that one fundamental cognitive mechanism underlies visual word identification, i.e., statistical learning. Human infants learn to chunk smaller perceptual units (e.g., oriented lines) into larger, meaningful objects (e.g., tools, faces), taking advantage of recurrent patterns in their distribution. As developing readers, they would apply this very same mechanisms to a newly–encountered type of visual objects, i.e., letters. On this basis, they would build progressively higher–order orthographic units, which eventually make their visual word identification as adult readers astonishingly efficient. The project is composed of four work packages. One aims at identifying which principle(s) drive(s) statistical learning, and contrasts overall frequency, contextual diversity, and letter transitional probabilities. Because these factors co-vary in real languages, a second work package will involve adult readers in learning artificial languages, where we will build in any statistical properties we might need to test. A third package will seek signs of statistical learning directly into the performance of developing readers. A fourth package will assess positional constraints in the identification of morphemes (e.g., kind and ness in kindness). These work packages include behavioural, eye tracking, ERP, MEG and fMRI work. Bringing together evidence from such a wide array of approaches will allow to understand how statistical learning unfolds, and what kind of representations it brings into the human reading system.

Mots-clés : reading,visual word identification,statistical learning,orthographic coding
Projet ERC : CosNeD (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Polytechnic University of Bucharest — Pays : Roumanie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 185925.0 €

Detection of cosmic neutrinos can answer very important questions related to some extremely energetic yet unexplained astrophysical sources such as: compact binary stars, accreting black holes, supernovae etc., key elements in understanding the evolution and fate of the Universe. Moreover, these particles carry the highest energies per particle known to man, impossible to achieve in any present or foreseen man made accelerator devices thus their detection can test and probe extreme high energy physics. One of the newest techniques for measuring high energy cosmic neutrinos regards their radio detection in natural salt mines. A first and essential step is to determine experimentally the radio wave attenuation length in salt mines, and this will represent the main goal of this project. The results shall be used to estimate the implications on the construction of the detector. The outcome of this project may rejuvenate the radio detection in salt technique and be a compelling case for Romanian involvement. The same measurements can be used: to validate and improve previous work on theoretical simulation models of propagation in heterogeneous media –a regime not very well understood (which represents another goal of the project), and to study the behavior of classical antennas in non-conventional media (the third major goal). The results to be obtained would be immediately relevant in determination of the key parameters that describe a cosmic neutrino detector, its performances and limitations. The events detected by such a telescope will allow identification of individual sources indicating a step forward in “neutrino astronomy”. The extensive propagation and antenna behavior studies in heterogeneous media will be in the direct interest for the scientific community and have a prompt impact in telecommunications theory and industry.

Mots-clés : radio wave propagation,multi layered medium,antenna
Projet ERC : GrowCELL (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : University of Edinburgh — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Determination of organismal size is a fundamental biological question. Vertebrate size is established based on total cell number generated during development. Despite the 75 million-fold difference in size between the smallest and largest mammals, the mechanisms for this remain to be determined. This proposal seeks insight into how total cell number is determined in both pathological and physiological states. Over the last decade our study of extreme growth disorders has identified 18 new human disease genes. We established these encode core components of the cell-cycle machinery, providing cellular and developmental insights into the pathophysiological mechanisms of these disorders. From our starting point of human disease, this approach also revealed novel genome instability genes informing fundamental research of basic biological processes. Still, the molecular basis for over half of individuals with microcephalic dwarfism remains unknown. This proposal will break new ground through the comprehensive application of Whole Genome Sequencing to our patient cohort to achieve screen saturation via identification of coding and non-coding mutations. Forward-genetic genome-wide CRISPR screens in developmentally relevant cell and organoid systems will also be developed to define key cellular processes impacting human growth. Beyond these ‘discovery science’ approaches, cellular and model organism techniques will be used to define the mechanistic basis for human disease caused by mutations in core replication machinery and key epigenetic factors. To extend prior work on pathophysiological mechanisms, we aim to establish a subset of microcephalic dwarfism genes as growth regulators, and thereby further define when and how organism size is determined. These studies will link essential cellular machinery governing proliferation with human disease, identify novel genome-stability factors and may yield insights into the developmental regulation of mammalian size.

Mots-clés : organism size determination,human genetics,mendelian disease gene identification,dna replication,genome stability,stem cells,dna methyltransferases
Projet ERC : CONNEXIO (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
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 : 1727731.0 €

Developing minimalistic biological neural networks and observing their functional activity is crucial to decipher the information processing in the brain. This project aims to address two major challenges: to design and fabricate in vitro biological neural networks that are organized in physiological relevant ways and to provide a label-free monitoring platform capable of observing neural activity both at the neuron resolution and at large fields of view. To do so, the project will develop a unique microfluidic compartmentalized chips where populations of primary neurons will be seeded in deposition chambers with physiological relevant number and densities. Chambers will be connected by microgrooves in which neurites only can grow and whose dimensions will be tuned according to the connectivity pattern to reproduce. To observe the activity of such complex neural networks, we will develop a disruptive observation technique that will transduce the electrical activity of spiking neurons into optical differences observed on a lens-free platform, without calcium labelling and constantly in-incubo. By combining neuro-engineering patterning and the lens-free platform, we will compare individual spiking to global oscillators in basic neural networks under localized external stimulations. Such results will provide experimental insight into computational neuroscience current approaches. Finally, we will design an in vitro network that will reproduce a neural loop implied in major neurodegenerative diseases with physiological relevant neural types, densities and connectivities. This circuitry will be manipulated in order to model Huntington and Parkinson diseases on the chip and assess the impact of known drugs on the functional activity of the entire network. This project will engineer microfluidics chips with physiological relevant neural network and a lensfree activity monitoring platform to answer fundamental and clinically relevant issues in neuroscience.

Mots-clés : microfluidics,neuro engineering,neural networks