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and tuning. Moderate research project experience training large-scale foundation models, especially pipeline/model parallelism. Track record of creating HPC software for numerical methods. Domain
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-scale foundation models, especially pipeline/model parallelism. Track record of creating HPC software for numerical methods. Domain expertise in areas like computational fluid dynamics, material
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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abilities Very good knowledge of magnetohydrodynamics, programming and numerical methods. Desirable qualifications, experience and knowledge Experience in stellar evolution theory and models. Desirable skills
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for large samples at ESRF ID16A using multislice tomography approaches. You will lead the development of and work with parallelized computer models to simulate how coherent waves travel through materials with