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Field
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on heterogeneous processor types Optimized GPU computing and exploitation of GPU architectures for HPEC (tensors, multi-GPU instantiations, advances in GPU for AI/ML) Compute-focused optimization of System-on-Chip
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California State University, San Bernardino | San Bernardino, California | United States | 7 days ago
within the California State University (CSU) system. Designed to advance machine learning and AI research, TIDE features a high-performance computing architecture built on GPUs, powerful processors, and
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, including CPU, GPU, storage, file systems, networking, visualization, job schedulers, and scientific applications. Understanding of specific technologies relevant to HPC applications such as AI, training
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data systems, including tools for automatic scaling, deploying, and managing of systems, e.g. Kubernetes ● Experience with Cloud Providers like Google, Azure, AWS ● Experience with GPU and
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transformer architectures (e.g., ViT/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g
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, including experience briefing sponsors and senior leadership Desirable Knowledge, Skills, and/or Abilities 1. Familiarity with high-performance computing (HPC) or GPU-based architectures 2. Active U.S
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, planner‑executor loops, or tool‑calling pipelines for complex decision‑making. Conducting adversarial testing, implementing input sanitization, and contributing to AI‑safety research. Utilizing GPU/TPU
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Center for Devices and Radiological Health (CDRH) | Southern Md Facility, Maryland | United States | about 21 hours ago
approaches for automated medical devices (e.g., physiologic closed-loop controlled devices). Developing multi-spectral computational modeling tools using GPU-based processors to map light propagation
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hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied
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, planner‑executor loops, or tool‑calling pipelines for complex decision‑making. Conducting adversarial testing, implementing input sanitization, and contributing to AI‑safety research. Utilizing GPU/TPU