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python), computational mechanics and fluid dynamics, numerical methods, machine learning, and the finite element method. In this position, the candidate will develop data-driven multiscale/multiphysics
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method. Proficient in python and C++ programming language. Special consideration will be given to candidates who are familiar with the open-source finite element library FeNiCS, brain finite element
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include processing to structure models of additively manufactured metallic and ceramic materials and structure to performance models based on the crystal plasticity finite element method and similar
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demonstration of relevant experience Preferred Qualifications Experience with finite element method Working knowledge of acoustics FLSA Exempt Full Time/Part Time Full Time Number of Hours Worked per Week 40
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, qualification, and deployment of AI agents and models, Computational Fluid Dynamics (CFD) simulation codes, and Finite Element Method (FEM) based tools for nuclear energy (fission and fusion
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, Finite Element Method, potential flow theory and Green's function formulations • Conformal mapping, in particular Schwarz–Christoffel transformations • Viscous-inviscid interaction and integral
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Proficiency in numerical analysis using finite element method (FEM) software (e.g., COMSOL, ANSYS, or custom FEM codes) Proficiency in one or more programming languages (e.g., MATLAB, Python, C++, Julia
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Proficiency in numerical analysis using finite element method (FEM) software (e.g., COMSOL, ANSYS, or custom FEM codes) Proficiency in one or more programming languages (e.g., MATLAB, Python, C++, Julia
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Element Method modeling (Abaqus, Ansys) or similar. 4. Basic familiarity with machine learning (preferred). 5. Some record of research output (e.g. peer-reviewed papers, conference abstracts) or
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electrolyser testing. Demonstrated knowledge/experience in some numerical methods such as lattice Boltzmann method, finite difference (element, volume) method, phase-field method. Demonstrated programming