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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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intelligent decisions. In particular, when low latency is critical, these models are deployed directly on devices at the edge, close to the equipment itself — a necessary condition for smarter, faster
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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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will equip 15 PhD researchers with cutting-edge expertise in combustion science, chemical kinetics, fluid dynamics, and digital modeling, preparing them to revolutionize industrial energy systems and
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utilization. DESIRE will equip 15 PhD researchers with cutting-edge expertise in combustion science, chemical kinetics, fluid dynamics, and digital modeling, preparing them to revolutionize industrial energy
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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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observations of the solar atmosphere, in-situ measurements from heliospheric probes, in synergy with a complete numerical modeling of the generation and propagation of solar jets from the solar atmosphere
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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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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