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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
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innovative tools combining high-fidelity simulations based on a Lattice Boltzmann Method (LBM) CFD code with advanced data assimilation techniques, notably the Ensemble Kalman Filter (EnKF). By integrating
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modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux/HPC environments Ability to conduct independent research and publish in peer-reviewed journals Strong written and
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decision is made Strong background in computational modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux
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, components, overall system performance) Numerical methods and simulation tools (e.g., Python/Matlab, CFD modelling, optimization) Beyond technical skills, we value people who contribute to a healthy and
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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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). The network joins 17 international academic institutions and 14 industry partners (https://euraxess.ec.europa.eu/jobs/401249 ). We work together in the field of fluid-structure interaction in technical systems
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computational fluid dynamics (CFD) and computer-aided design (CAD) software. They should also be prepared to engage in both computational analysis and experimental testing as required. Essential criteria
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PhD project is centred around advanced CFD modelling of liquid green fuel (methanol and ammonia) combustion under engine-like conditions, i.e., in a constant-volume combustion chamber (CVCC
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developing discrete element models (DEM) or hybrid models, such as DEM-CFD or DEM-SPH, is essential. For this position, a doctoral degree in a relevant discipline is required, although candidates nearing