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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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to capture experimentally due to the small scales and opacity of the matrix. Consequently, computational fluid dynamics (CFD) is the best approach for improving these burners. This PhD aims to investigate NH3
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exchangers (HX) for optimizing thermal storage in silos. The researcher will deploy conjugate heat transfer CFD models and conduct simulations to provide high-fidelity predictions of available power, charging
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modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux/HPC environments Ability to conduct independent
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The work involves extending CatalyticFOAM, a reactive CFD framework, for
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are seeking a Research Associate to develop a high-fidelity Artificial Intelligence (AI) framework for modeling
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) processes within the EIC PATHFINDER project PREDICT by unifying detailed physical models - light transport, surface reaction kinetics, and multiphase reactive flows - into a single CFD framework. The goal is
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian You will be part of a dynamic research team working on topics relevant
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simulation of fluid-structure interaction (FSI) with focus on the fluid mechanics. We couple computational fluid dynamics (CFD) to a structural solver and/or a controller for the detailed simulation of a
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Offer Description Completion of doctoral thesis related to: - Modelling of the geometry for the simulation of the detectors - Meshing of the geometry - CFD simulation - Analysis of the results