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, implementation, modernization, and operation of HPC environments built to solve complex computational challenges within highly secure classified environments. You will bring expertise in HPC architecture, cluster
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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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for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically
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are looking for candidates with extensive experience in HPC architecture, cluster management, and parallel computing, with a proven ability to work within highly secure and regulated environments
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, implementation, modernization, and operation of HPC environments built to solve complex computational challenges within highly secure classified environments. You will bring expertise in HPC architecture, cluster
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experience in HPC architecture, cluster management, and parallel computing, with a proven ability to work within highly secure and regulated environments. This role involves close collaboration with security
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distributed computing, machine learning, and architecture search, you will use leadership-class and exascale systems to evaluate and optimize new approaches. You will collaborate across disciplines, help
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we treat one another, work together, and measure success. Basic Qualifications BS degree in Computer Science, Cybersecurity, or related field. Minimum of two years of relevant experience. Preferred
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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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of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing. Author peer reviewed papers for internal and external release as