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Field
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that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute
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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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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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funding, Profs. Himanshu Gupta and CR Ramakrishnan conduct research in the general area of quantum networks, quantum sensor networks, and distributed quantum computing. The center includes other quantum
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essential. Prior experience in informatics/programming (Python, R) or omics data analysis is not required but a strong interest in developing these skills is highly desirable. Starting salary will follow NIH
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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 National Energy Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivatedPostdoctoral Researcher - HPC Workflow Performance (NESAP/NERSC) to join the Workflow
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distributions, cloud microphysical properties and processes, dust aerosol distributions and impacts, and atmospheric boundary layer (ABL) structure and dynamics. In recent years, we have focused on advancing
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
. Established in 1950, it was the first school of nursing in North Carolina to offer a four-year baccalaureate nursing degree program followed by the first master’s degree program, the first continuing education
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large-scale training and post-training pipelines (including distributed data/compute and evaluation harnesses). Collaborate with domain scientists and external partners; co-develop end-to-end AI workflows