137 structures-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" PhD positions in France
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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
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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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experimental measurements will be conducted to characterize key physical parameters, including temperature gradients, cooling rates, and surface and structural integrity, using multi-scale and Multiphysics
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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
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PhD student at ILL: studying In situ neutron diffraction for green steel and functional metal oxides
include oxides of chromium, iron, tungsten and the strongly correlated electron systems in SrFeO3−𝛿, LaNiO3 and SrRuO3. In situ neutron diffraction will allow to extract structural details including oxygen
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the developed analysis tools. You will join the Large Scale Structures (LSS) group at the ILL, Grenoble, France and work mainly with the two NR machines D17 and FIGARO for the implementation of the ML
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, to create a responsible and innovative university to serve as a model for the 21st century. Within ICN, the ChemSenSim group (https://lab.chemsensim.fr/ ) develops interdisciplinary research projects
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/ Partnerships Partners of the PEPR DIADEM – CINEMA project funding this PhD: IRCER, Institut P’, ILM https://www.pepr-diadem.fr/projet/cinema-2/ Scientific Field and Context The optimization of growth–property
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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
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electronic structure methods for the above-described properties. In more details, this will require the development of an automated approach that allows identifying the excited-states across several levels