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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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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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studentships are available. You will develop expertise in cutting-edge laser diagnostics or direct numerical simulation (CFD) for turbulence research. You will become expert in turbulent flow physics and will
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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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duties and responsibilities Carry out research in modelling and simulation of particulate processes using appropriate software packages for techniques such as DEM, CFD, FEA and Machine Learning. Develop
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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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at the university level; Expertise in CFD software (OpenForm, Ansys Fluent) andFEM software (ABAQUS, ANSYS, SAP2000) and coding (Python/MATLAB). Professional engineering licensure (HKIE/CEng
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on materials. Background (preferential): Materials science Additive manufacturing Metallic alloys Material characterization/Materials testing FEM/CFD simulations Additional background that will be valued in
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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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Doctoral (PhD) Candidate to join the new MSCA Doctoral Network FairCFD (https://www.imft.fr/faircfd/project-presentation/ ). The candidate will enrol for a PhD in Chemical Engineering at the University