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service offerings (e.g., large-scale geospatial compute pipelines, data ingest/curation/archive, analytics/visualization, user support). Establish operating policies, SLAs, user workflows, resource
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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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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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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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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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, 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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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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Organizational learning and technology proliferation Generate analytical assessments and technical products on emergent technological issues that are to be shared with counterparts, ORNL leadership, and sponsors
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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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laboratory investigations with inorganic mercury and methylmercury. Acquire and analyze data using a range of analytical instrumentation. Maintain detailed and accurate records. Prepare oral and written