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partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML Enhancement of AI/ML with in-network computing & processing Adaptation & optimization
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thick and strongly scattering samples. Experience in high-performance computing, parallel programming, or GPU-accelerated computation for large-scale 3D reconstruction. Experience applying machine
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Computer Science and related topics. The Department has more than 1800 students on bachelor level, 600 master students, and over 240 PhDs and postdocs. The overall staff of the Department is close to 370 employees
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