206 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Bournemouth University" uni jobs at Oak Ridge National Laboratory
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solutions to compelling problems in energy and security. The Data Science & Visualization Group at Oak Ridge National Laboratory (ORNL) advances AI/ML research and delivers applied solutions that support high
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subcontractor construction submittals and Requests for Information (RFI’s) to ensure timely responses and response durations are upheld. Inspect construction work for compliance with design requirements through
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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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or SolidWorks platforms to produce electrical schematics and equipment designs. Familiar with Allen‑Bradley automation hardware, National Instruments data‑acquisition platforms, or comparable industrial
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the planning of inspections and tests, and interpretation of data collected Proposes corrective actions to improve compliance with quality specifications Performs inspections and sets quality assurance testing
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requires the ability to obtain and maintain a Sensitive Compartmented Information (SCI) clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing
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. In addition to these responsibilities, the candidate will be a contributor to R&D projects that involve electro-mechanical systems and integrated data acquisition systems. In this position
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sensitive information. Primary duties will include development, documentation, implementation, and compliance assurance of the TSCM and TEMPEST programs. All team members deliver ORNL’s mission by aligning
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through multidisciplinary research, data analytics, modeling, engineering design, decision support, and visualization. The group develops innovative tools and technologies to enhance the efficiency
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Fuel Fabrication (PFF) Group as a highly motivated individual with expertise in applying advanced characterization technique and data analysis skills to coated particle fuels. The PFF group is dedicated