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lakes - Good knowledge of mathematical and statistical modeling methods in ecology - Proficiency in optical microscopy and flow cytometry tools - Very good knowledge of algal community identification
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27 Sep 2025 Job Information Organisation/Company CNRS Department Laboratoire d'analyse et d'architecture des systèmes Research Field Engineering Computer science Mathematics Researcher Profile
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for these formalisms. Some possibilities are to develop solutions based on dynamic programming over finite horizon, or using mathematical solvers, or adapting reinforcement learning algorithms to the desired context
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sciences, mathematics). IBENS is also strongly involved in training students and young researchers at all levels. The host team, led by Hervé Le Hir, includes 9 members and is part of IBENS's “Functional
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24 Oct 2025 Job Information Organisation/Company CNRS Department Institut d'électronique et des technologies du numérique Research Field Engineering Computer science Mathematics Researcher Profile
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5 Sep 2025 Job Information Organisation/Company CNRS Department Institut Pascal Research Field Engineering Physics Technology Researcher Profile First Stage Researcher (R1) Country France Application Deadline 25 Sep 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per...
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, bioenergetic, ecosystem and/or habitability modelling, strong mathematical skills and programming experience, and experience with analysis of observational and/or model-derived datasets. The CDD is offered for 2
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. - Knowledge in programming, data treatment, electron diffraction simulations, mathematical skills, knowledge about machine learning and artificial intelligence is a plus. Website for additional job details
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25 Sep 2025 Job Information Organisation/Company CNRS Department GéoAzur Research Field Geosciences Astronomy Environmental science Researcher Profile First Stage Researcher (R1) Country France Application Deadline 15 Oct 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours...
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) understanding of the mathematical foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on Neural Networks, 3) problem solving