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field or method, including, but not limited to, numerical methods, machine learning, or parallel and distributed computing. Expertise in a parallelization method (e.g., CUDA or ROCm, MPI, OpenMP
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Ability to work on multiple projects in parallel and rapidly adjust to changing priorities Proven ability to maintain productive relationships with faculty, researchers, students, and external collaborators
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accelerators, GPU, NPU, FPGA, distributed storage systems, software and hardware co-design, performance analysis, parallel processing, emerging architectures, and/or other advanced topics in computer engineering
Searches related to parallel computing
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