150 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" PhD positions in France
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, 12 (1), 4093 Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5629-JOAVIG-003/Default.aspx Requirements Research FieldChemistryEducation LevelPhD or equivalent Research
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filled. Shortlisted candidates will be invited to a remote interview in May 2026. About LAPTh (https://www.lapth.cnrs.fr ): LAPTh is a joint research unit (UMR) of CNRS and Université Savoie Mont Blanc
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to apply Website https://amethis.doctorat.org/amethis-client/prd/consulter/offre/2893 Requirements Research FieldGeosciencesEducation LevelMaster Degree or equivalent Skills/Qualifications Master’s degree in
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comprehensive platform for data extraction, analysis, and version control, providing access to highly curated datasets in a machine learning-friendly format. This PhD is part of the CARES project (Chemically
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law for strain gradient plasticity. Journal of the Mechanics and Physics of Solids, 46(3), 411-425 Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR7239-THIRIC-003/Default.aspx
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Redox Monolayer. Phys. Rev. Lett. 130, 218001 (2023). Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UPR8001-SIMGRA-002/Candidater.aspx Requirements Research FieldEngineeringEducation
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of theoretical although both will explore the interfaces between theory and experiment. They will both be hosted by the Quantum Information team (https://qi.lip6.fr/ ) of the Computer Science department (LIP6
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vision is also highly appreciated. The candidate must also have strong programming skills (Python, C++) and experience with ROS / MC_RTC (preferred). About MAVRICS The PhD is a part of the activities
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mathematical models using a reasonable number of physical variables; (2) the observations of extreme weather events used in the learning bases of DNNs are much rarer than those of standard events. This induces a
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the field of frugal or green AI TECHNICAL SPHERE You have a proven experience in frugal, green or low-resource AI Strong grasp of deep learning architectures (CNN, RNN, Transformers, LLMs). Experience in fine