54 structures "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" PhD positions at CNRS in France
Sort by
Refine Your Search
-
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
-
physical properties of thermal, combustion and detonation. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UPR3346-NADMAA-157/Candidater.aspx Requirements Research FieldEngineeringEducation
-
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
-
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
-
together expertise in physics, chemistry, nanoscience, and materials engineering. For more information about IS2M, please feel free to visit the website: https://www.is2m.uha.fr/ . The PhD candidate (M/F
-
to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR5798-NICBAC-009/Default.aspx Requirements Research FieldPhysicsEducation LevelMaster Degree or equivalent LanguagesFRENCHLevelBasic Research
-
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
-
Starrydata2). The work will include the implementation of machine learning models (neural networks, random forests, SISSO), generative approaches for predicting crystal structures, the use of machine learning
-
program, involving close collaborations with several French laboratories and NASA's Jet Propulsion Laboratory. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7326-ANAMEK-122/Candidater.aspx
-
. Argument(ation) mining, the new and rapidly growing area of Natural Language Processing (NLP) and computational models of argument, aims at the automatic recognition of argument structures in large resources