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thermo-electric devices onto non-planar metallic substrates. In a parallel track, the team will develop techniques for the design and manufacture of the structures with predictable material properties
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parallel and distributed systems, including performance tuning Programming and tooling such as C/C++, Python, CUDA, OpenMP, and Spack Linux-based systems, scripting, Slurm, and general systems engineering
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of computer graphics fundamentals, numerical methods, and GPU/parallel computing concepts. Experience with at least one major deep learning framework (PyTorch preferred). Excellent problem-solving skills and
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