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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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, and parallel computing, with a proven ability to work within highly secure and regulated environments. This role involves close collaboration with security teams, scientists, and IT leadership to ensure
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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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the world. This evergreen posting represents multiple potential openings across ORNL’s high-performance computing ecosystem. Successful candidates will help architect, deploy, and maintain HPC systems
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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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
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. Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, engineers, and physicists conducting basic and applied AI/DL research
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, monitoring, and tooling support across multiple clustered infrastructures, we facilitate Lab-wide R&D projects. Our HPC clusters range in scope from just a handful of nodes to over fifty-thousand cores. We
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challenges facing the nation. We are seeking a Signal Processing Engineer who will develop and deploy advanced sensing and communications systems for critical Energy and National Security applications.This
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developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation of results. Deliver ORNL’s mission by aligning