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the evaluation panel is obtained by assigning a weighting factor of 50% to the CV, and a weighting factor of 50% to the interview. Additionally, the evaluation panel retains the discretion to withhold
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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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elements of GPU streaming processors. Understanding of operating system constructs like threads, namespaces, process isolation, memory-mapped IO, asynchronous execution, and asynchronous IO. Comfortable in
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growing the use of high-performance computing in the research enterprise. ARCSIM is a component of the Office of the Vice President for Research and Dean of the Graduate School. The position will have an