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(Machine Learned Potentials) type approaches, and/or multi-objective approaches. - in-depth knowledge of Python programming languages (or C++, Fortran) and the Unix system; - Certified level in written and
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generation) and we need to develop innovative and efficient methods capable of processing an increasingly large mass of data, which is increasingly complex. The post-doc will work under the responsibility
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science » OtherEducation LevelPhD or equivalent Skills/Qualifications Candidates for the post-doc must hold a PhD degree in Computer Science, Robotics, Statistics, Applied Mathematics or a related field
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processing, involving machine learning techniques, as well as active participation in data collection from the detectors deployed on site. - Analysis of particle physics data applied to muography: filtering
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and machine learning Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR7018-CEDGEN1-002/Default.aspx Work Location(s) Number of offers available1Company/InstituteLaboratoire de
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in developing and applying niche models, and population models. Experience with machine-learning will be considered as a plus. Knowledge of paleogenomics, population genetics and isotope geochemistry
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Brain Barrier (BBB), CNS Drug Delivery, Brain Shuttles, Brain Imaging, Medicinal Chemistry, Computational Science, Artificial Intelligence (AI), Machine Learning. MAIN SUB RESEARCH FIELD OR DISCIPLINES1