253 machine-learning "https:" "https:" "https:" "The Open University" "The Open University" Postdoctoral positions at CNRS
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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computer scientist with experience in bioinformatics, solid programming skills and knowledge in 3D protein structures. Machine learning skills and knowledge of Web development are a plus. Good interpersonal
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part of the international Refuge-Arctic project (https://www.refuge-arctic.ulaval.ca ) with links to the NASA FORTE project, whose overall objective is to better understand and predict the role played by
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dynamical systems), epidemiological modelling, data analysis (statistics, machine learning). • in scientific programming (preferably Python, Matlab, R) Genuine interest in the analysis and modeling
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Eligibility criteria Instrumental optics and imaging (microscopy, camera detection) for biology. Skills in coding and experiment control. Basics of machine learning and/or signal processing. Teamwork
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, access to computer cluster Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8197-VALHER-212/Candidater.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent
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of errors between model predictions and post-operative reality This work will be carried out by the Biomécamot team (https://www.timc.fr/BiomecaMot ) at the TIMC laboratory, which is part of the CNRS's
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of adult CA1. Computer work Inmed is made up of 11 research teams, 5 platforms, and 3 shared resources, representing a total of 140 people. The agent will be based at the Luminy campus, in the Calanques
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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