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management, parallel computing, and performance optimization while helping evaluate and introduce emerging technologies that advance mission capabilities. You will work alongside a multidisciplinary team of
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. Experience with performance tuning and benchmarking tools for HPC environments (e.g., Ganglia, Grafana, or similar). Experience with parallel programming frameworks (e.g., MPI, OpenMP, CUDA) and high
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represent the organization by giving technical presentations to DOE program managers and in large public forums. Basic Qualifications: A PhD or equivalent experience in nuclear, mechanical, or chemical
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common scientific programming languages such as C++, Python, and/or Julia and version control systems. Experience in parallel programming with one or more common parallel programming models, like MPI
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, Python, or Ansible. Experience with performance tuning and benchmarking tools for HPC environments (e.g., Ganglia, Grafana, or similar). Experience with parallel programming frameworks (e.g., MPI, OpenMP
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requirements into scalable infrastructure solutions. Eligibility for access to Sensitive or Special Access Program information. Current Top Secret clearance with SCI eligibility. Preferred Qualifications
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improve the efficiency, dependability, and trustworthiness of scientific workflows, from traditional HPC and data pipelines to agentic workflows in which AI agents plan, execute, monitor, and adapt
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Unix environment In addition, prior experience working with parallel programming technologies including at least one of the following: MPI OpenMP CUDA HIP Kokkos Raja Preferred Qualifications: Experience
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strategic management and strict adherence to security protocols. We are looking for candidates with extensive experience in either classified HPC data center operations, architecture, parallel computing
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supercomputer to break the exascale barrier and Orion, a 700 petabytes Lustre parallel file system. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division also hosts