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-performance computing and/or large-scale data centers; Advanced experience with large-scale software development and support; Advanced knowledge of Linux kernel internals and systems programming methods
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new technologies. The ECE Department supports compute-intensive research areas. ECE Department represents a diverse range of needs, effectively leveraging centralized heterogeneous high-performance
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University Seattle campus. Course topics include High-performance Computing, VLSI Design , Advanced Machine, Learning Combinatorial Optimization and Statistical Inference. Responsibilities include
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working on the command line, including in a Unix/Linux environment Familiarity with high-performance computing (HPC) and high-throughput computing (HTC) environments and job schedulers such as SLURM and
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computing, and develop machine learning algorithms. With a passion for high-performance technology, large-scale machine learning, and AI-type algorithms, students become intuitive problem solvers
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, evaluation, and experimentation. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background in database systems
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develop machine learning algorithms. With a passion for high-performance technology, large-scale machine learning, and AI-type algorithms, students become intuitive problem solvers, experienced engineer
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PyTorch, including model training, fine-tuning, evaluation, and experimentation. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi
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initiatives. Team leadership and development: Lead, mentor and develop a high-performance team of IT professionals. Foster a culture of innovation, excellence and ongoing improvement. Business engagement
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electronic devices based on microbially produced protein nanowires. These biologically derived conductive materials enable sustainable approaches to energy harvesting, neuromorphic computing, and biosensing