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of capabilities such as AI training and inference at scale, and tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics
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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis
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for an accurate simulation of time-dependent flows, enabling sensitive applications such as aeroacoustics. Furthermore, the high scalability on massively parallel computers can lead to advantageous turn-around
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conferences. Engage in community knowledge-sharing (e.g. tutorials for the NERSC user base). What is Required: PhD awarded within the last five years in Physics, Computational Chemistry, Computational Science
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-reviewed venues and conferences. Engage in community knowledge-sharing (e.g. tutorials for the NERSC user base). What is Required: PhD awarded within the last five years in Physics, Computational Chemistry
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distributed systems techniques. Proficiency in programming languages such as Python, C++, or similar, as well as experience with HPC environments and parallel computing. Demonstrated hands-on experience and
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distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data management and
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tight AI-simulation coupling. What is Required: PhD in Physics, Chemistry, Computational Science, Data Science, Computer Science, Applied Mathematics, or a related numerical field. Programming experience
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software for multi-arch environments Development in high-performance computing (HPC) or distributed systems Strong understanding of Linux toolchains, build systems (CMake), and debugging tools Parallel
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software for multi-arch environments Development in high-performance computing (HPC) or distributed systems Strong understanding of Linux toolchains, build systems (CMake), and debugging tools Parallel