174 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" scholarships in France
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Field
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Website https://amethis.doctorat.org/amethis-client/prd/consulter/offre/3067 Requirements Research FieldGeosciencesEducation LevelMaster Degree or equivalent Skills/Qualifications The candidate should
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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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from the Resif-Epos consortium. Comptes Rendus. Géoscience, 353(S1), 381-412. doi: 10.5802/crgeos.98 Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR6118-GUIGUE-007/Default.aspx
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preserved by Christian institutions, following the example of research carried out by the ChrIs-cross team on documents preserved in Jerusalem. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant
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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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characterization of pictorial materials by isolating their signal and potentially identifying the techniques employed. Where to apply Website https://amethis.doctorat.org/amethis-client/prd/consulter/offre/3348
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colleagues on seismic hazard issues during regular visits to their offices. Where to apply Website https://amethis.doctorat.org/amethis-client/prd/consulter/offre/3059 Requirements Research
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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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the design and improve understanding of radiative transfer in practical TPV systems Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UPR8521-ALEVOS-008/Default.aspx Requirements Research
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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