423 machine-learning "https:" "https:" "https:" "https:" "The Open University" positions at CNRS
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to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR5300-GERLOO-006/Default.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Research FieldEnvironmental scienceEducation
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laboratory. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7281-AURBIM-054/Default.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research FieldBiological
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after thermal treatment to maintain gas flow and optimal detection. The PhD student will learn the synthesis of nanomaterials and their integration with 3D printing techniques. The synthesized materials
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astrophysics (completed by the start date), demonstrated experience in large-scale structure simulations, working knowledge of applications of machine learning techniques in cosmology and/or astrophysics (in
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statistical inference, machine learning and population genetics. The expected outcomes include new computational tools for studying B cell evolution, insights into age dependent immune diversity and the
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symplectic geometry: Baptiste Chantraine, Vincent Colin, Fabio Gironella, Stephane Guillermou, François Laudenbach, Rémi Leclercq. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR6629-FABGIR
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Université (Paris 05), in the team CONFID (COuches Nanométriques Formation Interfaces Défauts). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7588-JEACAN-002/Default.aspx Requirements Research
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https://emploi.cnrs.fr/Offres/CDD/UMR6614-THIBES-064/Default.aspx Requirements Research FieldEngineeringEducation LevelPhD or equivalent Research FieldChemistryEducation LevelPhD or equivalent Research
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conducted with Italian partners in Rome (Sapienza University, Catholic University of Rome, Gemelli Institute). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7252-VINCOU-006/Default.aspx
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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed