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strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems
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that benefits from and contributes to these advances. The division consists of six sections. Three sections, i.e., Diffraction, Spectroscopy, and Large-Scale Structures, are comprised of the neutron scattering
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electromagnetic transient models for bulk power systems, synchronous generators, large loads, etc. Develop simulation algorithms that enable large-scale simulations and/or AI/ML experience for intelligence in
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process knowledge to assign inventory data values to outgoing radioactive materials. Maintain records and control ledgers in accordance with stringent nuclear material accounting principles to accurately
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. Experience working with large environmental datasets such as flux tower and remote sensing data. Skills in statistically based model evaluation using observational data. Evidence of leadership potential
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computing solutions to efficiently scale testing environments supporting large datasets and high-performance AI workloads. Optimize resource allocation for simultaneous testing tasks and real-time tracking
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that documentation is accurate, clear, and supports downstream work activities. Technical Contribution Review analysis results and testing data for targeted machine design advancements. Approve design drawings and
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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A BS in computer science, data science, artificial intelligence, business analytics management
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them the ability to work with classified systems and information. Major Duties/Responsibilities: Work independently to provide quality assurance support for implementation of a graded approach to quality
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applying large language model (LLM)–based artificial intelligence tools (e.g., ChatGPT, Copilot, Claude). Some knowledge of fundamental concepts in data science, modeling, and data visualization. Familiarity