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characterization, mechanical testing, 3D microstructural analysis, finite element simulations, atomistic modeling, and thermal transport measurement techniques to advance mechanistic understanding and predictive
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) advanced Finite Element (FE) analysis with particular emphasis on the use of LSDYNA for simulation of crash analysis and roadside safety. This work increasingly emphasizes reliability-based performance
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science, or a closely related field. Experience with the finite element method. Proficient in C++ and Python. Skilled in Unix-based operating systems. Skilled in oral and written communications and presentations
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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, computer science, or a closely related field. Coding experience for the computational modeling of physical and/or engineered systems, preferably with finite-element methods, is a must. Strong programming
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of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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Responsibilities: Analyze variety of engineering problems using traditional analytical methods and finite element analysis packages to prove designs meet established design standards. Provide hand calculations
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working in radiological environment. Experience in heat transfer and thermal modeling/simulation using finite-element analysis (FEA) or other software. Ability to work within a multi-disciplinary team