249 machine-learning "https:" "https:" "https:" "https:" "The Open University" research jobs at CNRS in France
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and erosion for 60 years. One of the main objectives is to acquire fundamental knowledge about the processes controlling environmental risks related to the dynamics of metal contaminants (speciation
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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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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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UMR 6524, Clermont-Auvergne University. Collaboration with the IMFT (Institute of Fluid Mechanics, Toulouse) for the numerical modelling. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6524
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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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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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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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of European projects (GUINEVERE, FREYA, MYRTE) or bilateral CNRS-SCK collaborations (MYRACL, SALMON). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6534-AURGON-050/Default.aspx Requirements
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, MYRTE) or bilateral CNRS-SCK collaborations (MYRACL, SALMON). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR6534-AURGON-049/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD
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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