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unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In
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, or deployment at scale. A proven track record of high-quality research contributions published in top-tier machine learning conferences or journals. Proficiency in high-performance computing, distributed and
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linear algebra computations, building software for scientific applications using GPUs (Graphics Processing Unit), multi-threading and parallelism, numerical discretization methods (finite differences
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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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programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or large-scale data centers