392 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" positions at CNRS
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) - Signal processing and image analysis (Python) - Oral presentation of scientific results at meetings and international conferences. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5295
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specialist for the formulation of model soft media. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5295-MATMAL-001/Default.aspx Requirements Research FieldEngineeringEducation LevelMaster
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commensurate with experience and follows national academic standards for postdoctoral researchers. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR9019-NATPET-006/Default.aspx Requirements Research
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to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7261-AICBEL-048/Default.aspx Requirements Research FieldBiological sciencesEducation LevelPhD or equivalent Research FieldEnvironmental
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or by car (parking available). Public transportation costs are partially covered. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7104-MARMEN-001/Default.aspx Requirements Research
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their spatial patterns in varying environmental conditions. The successful candidate will integrate to the research unit « Microbial Oceanography - LOMIC : http://lomic.obs-banyuls.fr » in Banyuls sur mer, and
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Université (Paris 05), in the team CONFID (COuches Nanométriques Formation Interfaces Défauts). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7588-JEACAN-002/Default.aspx Requirements Research
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conducted with Italian partners in Rome (Sapienza University, Catholic University of Rome, Gemelli Institute). Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7252-VINCOU-006/Default.aspx
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on the interaction between human cognition and language—understood as a cognitive entity, a means of communication, an object of learning and lifelong development, and a sociocultural phenomenon. Mission : Background
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, L. Estel, Analysis of thermal runaway events in French chemical industry, Journal of Loss Prevention in the Process Industries, 62 (2019) 103938. https://doi.org/10.1016/j.jlp.2019.103938 2. Y. Wang