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Qualifications: Ph.D. in electrical engineering, computer science, or related discipline completed within the last five years. Demonstrated expertise in computed tomography (CT), with experience in sparse-view and
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Science, Computer Science, Applied Mathematics and Statistics, Electrical and Computer Engineering, Biomedical Engineering, or a related field. Experience with a deep learning framework like PyTorch. Strong
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understanding of critical infrastructure resilience, specifically improving access to electrical power for climate resilience and grid security. Your research will help to inform investments in grid resilience
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production target materials. This involves the development of experimental plans to examine material properties such as thermal diffusivity, thermal conductivity, and thermal expansion – material properties