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)* Strong background in computational mechanics and numerical methods Demonstrated experience with LS-DYNA or comparable commercial FEA software Proficiency in Python programming for scientific computing and
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Demonstrated experience with LS-DYNA or comparable commercial FEA software Proficiency in Python programming for scientific computing and machine learning applications Experience with machine learning methods
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involve established software tools, such as: CHEMKIN-PRO for steady one-dimensional simulations of laminar flames with detailed chemistry. CONVERGE for unsteady three-dimensional simulations of turbulent
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