138 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" PhD positions in France
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mechanics, inert, anisothermal and reactive fluids, to effects related to complementary physical properties of thermal, combustion and detonation. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre
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to complementary physical properties of thermal, combustion and detonation. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UPR3346-NADMAA-156/Candidater.aspx Requirements Research
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 1 month ago
. Picchini. Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings. Transactions on Machine Learning Research, 2024 Kugler, F. Forbes, and S. Douté. Fast
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of internal reports, articles, patents, and communications. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5635-DAMVOI-021/Candidater.aspx Requirements Research FieldChemistryEducation LevelPhD
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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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natural organic matter well characterized extracts (IHSS), the study will be performed on real water resources. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8516-JUSCRI-009
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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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-month programme focused on scientific excellence, innovation, and societal impact. The programme will provide training in relevant aspects of biology, physiology, physics, mathematics, computer and social
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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