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electrolysis and fuel cells (SOEC and SOFC). By combining numerical modeling with data-driven approaches, you will identify optimized operating conditions and strategies to improve both steady-state and dynamic
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. This approach aims to enable the development of computationally efficient models for simulating radiative transfer in three-dimensional cloudy atmospheres. Where to apply Website https://emploi.cnrs.fr/Candidat
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order to better understand, explain and advance society and environment we live in. Your role The PhD student will develop and apply computational multiscale models to investigate brain energy metabolism
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modeling with data-driven approaches, you will identify optimized operating conditions and strategies to improve both steady-state and dynamic performance in fuel cell (biogas) and co-electrolysis
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, multiphysics simulations, device implementation, and experimental validation. Key responsibilities: Develop theoretical and numerical models of piezoelectric energy harvesters under heavy-load conditions. Design
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improve the parameterization of rheology integrated into current large-scale sea ice models, particularly those used for real-time forecasting and/or in the context of coupled climate simulations
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developed simulation models in open-source toolboxes such as OpenFAST. For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base.
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of turbulent combustion models. Particular attention will be given to providing a well-characterized experimental reference case for numerical simulation and model benchmarking. The primary host institution is
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evaluate earlier developed friction models and extend them to account for effects such as slip direction and temperature dependence. Implement the developed models in commercial forming simulation software
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corrosion-fatigue conditions by integrating multiscale physics-based models combined with mesoscale experimental tests. This research will study the effects of corrosion-induced changes in composition