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release and represent the organization by giving technical presentations in large public forums. Basic Qualifications: Requires a Ph.D. with a minimum of 6 years of relevant experience, a M.S. with a
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performance, reliability, and scalability for large-scale computational workloads. Diagnose complex hardware and software issues, coordinating with vendors and internal engineering teams to implement solutions
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to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information sciences to enable quantum computers
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Language Models (LLMs). Distributed Machine Learning: Specialization in data parallelism, model-parallelism, and collective communication strategies in large-scale environments. Proficiency in frameworks
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engaging government agencies to capture sponsored research programs. Experience managing medium/large research projects and presenting project results. Experience managing/mentoring students or researchers
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U.S. and international export control regulations, including all United States export agencies (Energy, Commerce, State, Nuclear Regulatory Commission, and Treasury) and international control regimes
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of compute- and data-intensive computing environments, partnering closely with system vendors, national laboratories, and the broader HPC research community to shape the trajectory of leadership computing
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methodologies as well as subsized mechanical testing methodologies on highly irradiated materials (either using ions or research reactor irradiation data) for establishing performance envelopes for materials
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research user workflows. Preferred: experience with geospatial data workflows, including large geospatial/raster/vector datasets, spatial ETL pipelines, and performance considerations for geospatial
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across ORNL’s high-performance computing classified ecosystem. Major Duties and Responsibilities: Provide technical leadership in the design, integration, and administration of large-scale Linux-based HPC