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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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, finite volume, and machine learning to solve challenging real-world problems related to structural materials and advanced manufacturing processes. The successful candidate will have experience with
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systems, high-speed parallel file systems, and archival solutions critical to advancing scientific discovery and innovation. As part of ORNL’s leadership-class computing ecosystem, you will play a vital
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and machine-learning-driven optimization frameworks for polymer composite manufacturing processes. This position resides in the Composites Innovation Group in the Manufacturing Science Division (MSD
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frameworks to maintain secure and compliant environments. Document system architectures, processes, and best practices, and contribute to internal knowledge sharing. Participate in on-call rotations and off
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compliance, reproducibility, and interoperability across scientific domains. By improving data readiness processes, this role will amplify the potential of AI-driven discovery in areas such as high energy
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and clustered computing services to researchers who process large data sets and/or develop code as a part of their project. Ensure the availability, performance, scalability, and security of production
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Lustre parallel file system. NCCS serves multiple agencies including DOE, NOAA, and the Air Force. The NCCS also supports the center’s Quantum Computing User Program (QCUP) which provides access to state
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, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in
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, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together