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E-mail didier.josselin@cnrs.fr Requirements Research FieldGeographyEducation LevelPhD or equivalent Skills/Qualifications • PhD degree required • Strong interest in transport and mobility issues
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of 3D crystalline structures; – depending on the candidate's profile, implementing machine learning methods (AI & machine learning) for the analysis of physicochemical data from the hpmat.org database
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24 Feb 2026 Job Information Organisation/Company IMT - Institut Mines-Télécom Research Field Computer science » Database management Researcher Profile First Stage Researcher (R1) Positions PhD
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 9 days ago
skills Specific Requirements The candidate must hold a PhD in machine learning and have strong mathematical skills. Knowledge of bandit models is a plus. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood
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automated configuration mechanisms based on fingerprinting and machine learning to ensure traffic analysis remains faithful to the behavior of the monitored machines. Finally, you will validate your solutions
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Information Eligibility criteria Applicants should hold a PhD in theoretical chemistry, physics, materials science, or a related field; -demonstrate strong expertise in machine learning (regression, neural
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Website https://emploi.cnrs.fr/Offres/CDD/UMR5267-DOMCAI-002/Default.aspx Requirements Research FieldLanguage sciencesEducation LevelPhD or equivalent Research FieldLanguage sciencesEducation LevelPhD
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research centre dedicated to understanding normal and pathological brain function and developing new diagnostic and therapeutic approaches. Website: https://neurosciences.univ-grenoble-alpes.fr You will be
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, probability, and statistical learning. You must also be proficient in Python and speak English. You have a PhD or equivalent degree and are able to work in a team, communicate effectively, and write clear
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on the ERC-funded project ‘Understanding the Consequences of Major Health Crises for Education: Learning from the COVID-19 Pandemic (LEARN)’. The LEARN project: Health crises, natural disasters, and violent