266 machine-learning-"https:" "https:" "https:" "RAEGE Az" Postdoctoral research jobs at CNRS in France
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team at the Laboratoire d'Informatique de Grenoble (LIG). GetAlp conducts research in NLP, machine learning, evaluation, and interpretability. The project will be supervised by Maxime Peyrard (CNRS
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TCAD (Technology Computer Aided Design) simulation desirable. - Experience in power electronics desirable Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR8001-DAVTRE-003
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the hierarchical authority of Laurence Talini. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR125-LAUTAL-001/Candidater.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent
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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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the team 'Structural and Magnetic Properties of Materials. Four EPR spectrometers are available, in addition to three laboratories where sample preparation can be realized. Where to apply Website https
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model's development. The position is based at LOCEAN on the Pierre and Marie Curie campus of Sorbonne University. The LOCEAN laboratory (https://locean-ipsl.upmc.fr ) is one of nine laboratories in
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for the rapid and effective treatment of severe traumatic wounds, particularly in civil or military emergency situations. This new system aims to combine strong adhesion in wet environments, on-demand UV
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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Numerical simulations Analysis of experimental data Laboratoire Jean Perrin Theory group Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8237-RAPVOI-006/Candidater.aspx Requirements Research
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on the plants Arabidopsis thaliana will generate maps of depolarization, retardance, dichroism, and optical axis azimuth, which will feed machine learning models developed by the project partners to identify