147 structures "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD positions in France
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still know too little about what SME-appropriate control configurations look like, and how coordination across value-chain partners can be steered. This PhD project investigates how SMEs structure
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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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, 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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at the Center for Theoretical Physics in Marseille, France. Wikipedia is the classical example of a successful, large-scale collaborative project. Its production, structure and functioning have emerged through
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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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SyMulDaM project involving the development of predictive models to quantify the integrity and durability of a nuclear power plant containment structure., within the mechanical engineering department
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and the caprock. While chemo-hydrodynamic pattern formation has been extensively studied in porous media, for instance in polymers, its implications on the deformation and structural integrity of solid
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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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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