162 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD scholarships in France
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strong attention on emotion analysis. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7271-SERVIL-001/Candidater.aspx Requirements Research FieldComputer scienceEducation LevelPhD
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“Sustainable farming” funded by AGRALIFE (https://www.inrae.fr/Agralife ) and the project “Associations between human interventions (including those impacting wildlife) and animal disease spread and means
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, coordination, quality & popularity. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7332-CATLEV-056/Candidater.aspx Requirements Research FieldPhysicsEducation LevelMaster Degree or equivalent
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understanding of the deposition process/film physical chemistry/optical properties relationships Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5266-FREMER-003/Candidater.aspx Requirements
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. Currently available topics, application and more information: https://phdquantumgrenoble.univ-grenoble-alpes.fr/phd-application/available-phd-subjects PhD subjects (full list available via the attached link
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Mulhouse, France (http://www.is2m.uha.fr/ ) under the direction of Dr Valeriy Luchnikov, a member of the “Wetting and Self Assembly” research group, and Prof Thierry Vandamme, Faculty of Pharmacy of
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, and secondments at leading academic and industrial partners across Europe (Italy and Netherlands for this PhD offer). More information : https://cordis.europa.eu/project/id/101227338 •Master’s degree
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), UMR 7053, Nancy, FranceCountryFranceCityVandœuvre-lès-NancyPostal Code54500Geofield Contact City Vandoeuvre les Nancy Website http://www.l2cm.univ-lorraine.fr/l2cm/?page_id=53&%3Bcategorie_actualites
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
of material deposited, while maintaining the expected accuracy. Part of the activity will also involve implementing Artificial Intelligence (AI) methods similar to computer vision to facilitate this prediction
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SAF combustion. Recent advances have demonstrated that machine learning techniques, particularly neural networks, can significantly accelerate chemical kinetics computations. Nevertheless, most of