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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs
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developing machine learning surrogates and emulators for dynamical systems. Proficiency in managing large datasets and training with GPU-enabled computing resources. Expertise in numerical optimization and
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partners, and other national laboratories. Objective: Enhance THAPI: Extend and optimize the THAPI profiler (https://github.com/argonne-lcf/THAPI ) to concurrently profile AI/ML and ModSim components
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interests Three letters of reference More details on the CPAC group can be found on our website: https://cpac.hep.anl.gov Completed applications will be reviewed as received, with all applications submitted
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encouraged. More details on the CPAC group can be found on our website: https://cpac.hep.anl.gov Applicants should send: Curriculum vitae Brief statement of research interests Qualified candidates will be
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of funds. Relevant Publications: 1. P. Chen et al ., Ultrafast photonic micro-systems to manipulate hard X-rays at 300 picoseconds, Nat Commun, 10:1158 (2019). https://doi.org/10.1038/s41467-019-09077-1 . 2
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The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to build a physics