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to begin September 1, 2025. We will consider strong candidates in any research area but will prioritize Distributed and Parallel Computing. A PhD in computer science or a related area is required
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Research Scientific Computing Center (NERSC) is inviting applications for the position of Storage Systems Group (SSG) Lead. NERSC's mission is to accelerate scientific discovery through high performance
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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of relevant experience in Linux systems administration or HPC systems engineering. Preferred Qualifications Demonstrated experience leading the design and deployment of HPC or large-scale distributed computing
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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                The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 days ago
and Experience: Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models, HITL techniques, and prompt engineering. Experience with LLM fine-tuning
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programming, parallel computing, and bioinformatic and statistical genetic software packages. Experience in working with genomic and proteomic data available for large extended pedigrees. License
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management, cache optimization, and vectorization techniques. Strong understanding of algorithms and data structures, especially those suitable for parallel processing and distributed computing. Understanding
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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the creation of analytical reports to achieve client, program, and business objectives for resource optimization. Work closely with internal technology teams and vendors to deliver tools and system solutions