367 machine-learning-"https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" positions at CNRS
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ability to promote research: oral presentations and publications Ability to work in a team on multi-disciplinary projects Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR9012-MARLOU-064
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metabolic vulnerabilities in MB and thus, may pave the way to the development of promising therapeutic avenues in the worst outcome MB subgroup. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant
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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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fluid. The developments will be applied to various case studies such as supercritical CO₂ Brayton cycles, refrigeration cycles, and heat pumps. Where to apply Website https://emploi.cnrs.fr/Offres
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of sorption phenomena in these systems. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5253-PHITRE-003/Default.aspx Requirements Research FieldChemistryEducation LevelMaster Degree
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recreation, ticket sales, etc.) Health Insurance: Mandatory enrollment (unless exempt) in the MGEN plan, with 50% coverage Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8004-PAUBAR-010
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The expert will participate in the necessary methodological developments and analyses of airborne data recorded by the IAGOS research infrastructure (https://www.iagos.org ) and from other networks, to provide
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forces on each mode in order to reduce (i.e., cool) their individual vibrations. The student will be closely guided by the advisors and will acquire both theoretical and experimental skills
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Jupiter's polar regions using computer simulations. The core of the project consists of coupling a photochemical model (developed and used in numerous planetary applications) with an electron transport model
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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