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turbulent plasmas and by phenomenological models. The overarching goal of this ambitious programme is to describe the acceleration process across length scales, in the turbulent flow, in the inner jet and in
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correlations or more innovative methods of multivariate analysis and we anticipate here an opportunity of using machine learning that could help in predicting properties or classifying sources. A last step will
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particular NLP, statistical learning, machine learning, generative AI, and their major fields of application. Roles and responsibilities The applicant will join the team of the 3IA Côte d’Azur Institute and
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chemistry, materials science or equivalent having carried out research in an experimental field related to the thesis. Core competencies: crystal growth thermodynamic modeling chemical and physical
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modeling. Each PhD will lead to a double degree awarded by two partner universities, preparing graduates to become leaders in Europe’s energy transition. DC7 PhD Position "Uncertainty Quantification
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metabolism in type I interferonopathies within tissues. Using mouse models of these diseases, we will analyze how metabolic alterations contribute to inflammation and tissue damage. We will generate lipidomic
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of electrical topologies (AC, DC, three-phase) and will integrate both standard and atypical wear cases. On this basis, high-performance artificial intelligence models will be developed. By combining neural
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modelling or numerical simulations. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7342-MARBRA-012/Candidater.aspx Requirements Research FieldEngineeringEducation LevelPhD or equivalent
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particles - in promoting inflammation and fibrosis, and work to identify specific biomarkers of exposure and associated risks in human and mouse models. Develop and evaluate therapeutic strategies to target
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funded by the French National Research Agency (ANR) and involves five partners: the BSC – UMR7242 laboratory, the IGBMC (UMR7104) and TBI (INSA Toulouse) for molecular modeling, as well as the LSMIS