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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are seeking a Research Fellow to lead the development and
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opportunities offered by cutting-edge CFD methods. Prior experience in CFD and/or CFD code development (e.g., Python, Fortran, C++) would be a considered as a strong asset. Selection process The recruitment
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a new product to market. As a CFD Engineer, you will develop, run, and interpret detailed simulations of our novel membrane modules and other process technologies. You will engage in a cross
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about shape optimization and the new opportunities offered by numerical design in turbomachinery. Prior experience in CFD and/or CFD code development (Python, C++, Fortran) would be a significant
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foundation in fluid mechanics and heat transfer Experience with numerical methods (CFD or FVM) Programming skills (e.g. Python, MATLAB, C++, Fortran) Interest in machine learning and data-driven modeling
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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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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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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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proficiency in English. Documented experience in CFD and numerical modeling, preferably with OpenFOAM, Nek5000, or LBM. Strong programming skills (C++, Python, or similar). Ability to work independently and