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, and data science and analytics. Preferred Qualifications: Experience leading teams and performing research in artificial intelligence / machine learning, specifically for cybersecurity, signal
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analytics that enhance and evolve business operations and scientific decision-making capability and related activities at ORNL.Qualified applicants will have a solid foundation of Generative AI and Machine
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the Field Intelligence Operations Division within the National Security Sciences Directorate at ORNL. Major Duties/Responsibilities: Produce peer-reviewed papers and briefings of analytical assessments
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portfolio includes materials science and engineering, chemistry, geoscience, nanoscience, soft matter science, analytical chemistry, and nuclear and particle physics applied to a broad range of scientific and
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expected to contribute to the development and application of advanced manufacturing simulations, and machine learning (ML) models relevant to additive manufacturing, virtual manufacturing, material
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, and compliance requirements. Strong aptitude for computer systems, electronic tools, and digital workflows. Ability to learn and adapt to new technologies, including AI-enabled tools used to support
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information. Effective written and verbal communication skills. Analytical mindset with interest in workforce data and reporting. Ability to manage multiple priorities in a structured, deadline-driven
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of quality initiatives, assesses satisfaction, and exchanges feedback and lessons learned. Analyze, interpret, and communicate quality and performance data to management in support of established metrics and
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classified analytic products, following community trade‑craft guidelines. Learn the fundamentals of intelligence analysis through core training courses (provided). Travel domestically a few times per year for
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center workload trends, Deep Learning (DL) research, analyst reports, competitive landscape, and token economics Cluster Management and Optimization: Oversee the installation, configuration, and management