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within the D2-FTC department, Fluids, Thermal and Combustion, which corresponds to a continuum ranging from fluid mechanics, inert, anisothermal and reactive fluids, to effects related to complementary
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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
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of the trained models [4,5]. The resulting surrogate models will enable fast prediction of effective mechanical properties and deformation fields for complex microstructures, thereby providing an efficient bridge
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 28 days ago
information, as well as an analysis chain to instantiate and use models on open-source and industrial case studies. Outcome The project will propose a methodology to realize code migration of a niche technology
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: Background: Chronic kidney disease (CKD), which affects 8 to 10% of the population, is a major public health issue associated with an increased risk of cardiovascular disease. Diet and physical activity
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). - Knowledge in biophysics/spectroscopy and redox chemistry. - Personal skills: rigor, autonomy, and interest in multidisciplinary work. Ability to work in a team and to communicate effectively in written and
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on their relative importance or the existence of a dominant mechanism (e.g., Craig et al., 2016; Mazzotti et al., 2000; Damon et al., 2023; Grosset et al., 2023). To address this issue, the PhD thesis will comprise
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these factors, stress—whether psychological or environmental—has emerged as a key but still poorly understood modulator of inflammation, pain, and tissue homeostasis. Rather than being solely a consequence of
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tangible the information (effects of the disease and treatment, engagement, etc.) by adapting it to the pathologies, representations, and specific needs of each patient; 2) Support sustainable behavioural
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) offer a solution by integrating physical laws with complex data. However, their effectiveness is still hindered by uncertainties related to both data and models. Strengthening their robustness requires