312 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Postdoctoral research jobs in France
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rue Albert EinsteinGeofield Contact City Nice Website https://univ-cotedazur.fr Street 28 av de valrose Postal Code 06100 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share
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proximity labeling is expected. Experience in confocal imaging and/or super-resolution microscopy would be a plus. The proposed research will be supervised by Dr Marie Prevost (https://research.pasteur.fr/en
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Host Lab our lab (https://research.pasteur.fr/en/team/cellular-plasticity-in-age-related-pathologies/ ) explores how cellular senescenceorchestrates tissue repair and regeneration. We focus on how
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available1Company/InstituteInsitut des Sciences MoléculairesCountryFranceState/ProvinceGirondeCityTalencePostal Code33400Street351, cours de la LibérationGeofield Contact City Talence Website http://www.u-bordeaux.fr
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of the project is to exploit such data to develop generative models for aptamer design. The candidate is expected to have a strong background in machine learning and statistical physics, with a real interest for
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“Anthropologie et Histoire des Mondes Antiques” – UMR 8210CountryFranceState/ProvinceIle de FranceCityParis / Aubervilliers Geofield Contact State/Province France City Paris Website https://www.ephe.psl.eu/ Street
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DRESCountryFranceGeofield Contact City Strasbourg Website https://www.unistra.fr/ Street 4 rue Blaise Pascal Postal Code 67000 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket
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. The successful candidate will be employed at the Department of Computer Science of the University of Luxembourg and have access to high-performance computing resources suitable for large-scale machine-learning and
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, biology, computer science or related disciplines Strong computational skills, including machine learning, e.g. demonstrable project in a relevant field A strong first-author publication record in a relevant
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring