253 machine-learning "https:" "https:" "https:" "https:" "U.S" "U.S" research jobs at CNRS
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, depending on the start date. To apply, candidates must submit: 1) A detailed CV with a list of (pre)publications 2) A cover letter 3) A research proposal Where to apply Website https://emploi.cnrs.fr/Offres
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preparation platform, SSMIM - Resources provided (equipment, IT, etc.): Computer workstation, binocular magnifying glass, analytical equipment (IRMS mass spectrometer) Where to apply Website https
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elucidating the molecular and cellular mechanisms of the late phase of long-term potentiation (LTP), a key process in learning and memory. The project is based on the development and use of an innovative
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confirmation. About LAPTh (https://www.lapth.cnrs.fr ): LAPTh is a joint research unit (UMR) of CNRS and Université Savoie Mont Blanc (USMB). Its scientific activities span cosmology and astroparticle physics
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numerical results with observations from scanning and transmission electron microscopy provided by the partners of the ANR project IMP3D (https://anr.fr/Projet-ANR-24-CE08-3737 . - Select a discrete
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collaboration between the Exa-SofT and the Exa-DI projects and better support multi-linear algebra and tensor contractions in exascale CSE applications and Machine Learning. As part of the collaborative process
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Pyrenees. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5563-YOADEN-001/Candidater.aspx Requirements Research FieldGeosciencesEducation LevelPhD or equivalent Research
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, and optical glasses and fibres dedicated to the mid-infrared. State-of-the-art experimental equipment is part of the Equipex+ 'SMARTLIGHT' platform. Where to apply Website https://emploi.cnrs.fr
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) and high mass (>100 GeV). More details about the team in https://www.cppm.in2p3.fr/web/en/research/astroparticles/index.html#Dar… The candidate will be involved in all experimental aspects, from
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to conduct his own research projects if the scientific scope is compatible with the ERC ATTRACTE (modulo machine time). This position is funded by the ERC Starting Grant ATTRACTE project (2023-2028, PI: G