166 machine-learning "https:" "https:" "https:" "University of St" PhD positions in France
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months 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 sorption phenomena in these systems. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5253-PHITRE-003/Default.aspx Requirements Research FieldChemistryEducation LevelMaster Degree
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, deformation mechanisms and mechanical performance, ultimately enabling more efficient design and optimization of advanced structural materials. [1] https://www.pepr-diadem.fr/projet/ammetis-2/ [2] https
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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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6 Mar 2026 Job Information Organisation/Company UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE Department Computer ingineering Research Field Engineering » Computer engineering Researcher Profile First
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by the Simons Foundation’s grant ``Probabilistic paths to Quantum Field Theory’’, started on September, 1st 2025 https://probabilistic-qft.org/ . Applicants must hold an excellent master’s degree in
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that give rotaxanes the ability to produce reactive oxygen species, and applications of these architectures in antibacterial photodynamic therapy. Where to apply Website https://amethis.doctorat.org/amethis
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 2 months ago
) the exploration of mixed-precision arithmetic in the context of high-order discontinuous discretization methods, and (2) the integration of machine learning techniques to complement and enhance traditional
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, deformation mechanisms and mechanical performance, ultimately enabling more efficient design and optimization of advanced structural materials. [1] https://www.pepr-diadem.fr/projet/ammetis-2/ [2] https