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datasets. Experience with GPU-based training and high-performance computing. Interest in translating methodological contributions into high-impact medical AI venues (e.g., Nature Medicine, Nature Machine
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 5 hours ago
with rotorcraft aerodynamics, comprehensive analysis tools, or high-order unstructured solvers Experience with GPU-accelerated CFD workflows Point of Contact Mikeala Eligibility Requirements Degree
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. Experience with GPU-based training and high-performance computing. Interest in translating methodological contributions into high-impact medical AI venues (e.g., Nature Medicine, Nature Machine Intelligence
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• Execute large-scale simulations on CPU and GPU-based HPC clusters • Analyze results, generate technical reports, and deliver project outcomes on schedule • Prepare scientific reports and publish in
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adaptive optimization during needle insertion, integrating live ultrasound imaging with GPU-accelerated dose calculation and optimization. The Postdoctoral Research Associate will join a multidisciplinary
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scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation Experience applying machine learning or AI to molecular simulation
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hardware architects to establish how agentic AI and these languages co‑design with heterogeneous HPC systems (CPUs, GPUs, PIM, AI accelerators). Study performance and portability tradeoffs, leveraging
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on small test clusters. Test computational performance and resolve technical challenges on significantly larger models of selected quantum materials. Work on speeding up Krylov solvers on GPUs. Demonstrate
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computing environments, and GPU programming. Necessary skills include knowledge of data processing using software (e.g., Matlab, R, IDL) and/or statistical/mathematical programming languages (e.g., R, Matlab
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI