262 linked-data-"https:" "https:" "https:" "University of St" positions at Oak Ridge National Laboratory
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Laboratory (ORNL). As part of our team, you will investigate the atomic and electronic structures in energy and quantum materials and correlate them with relevant properties for energy and data storage
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, mentorship of junior staff, and the ability to influence program direction through data-driven engineering judgment and recognized subject-matter expertise. Key Responsibilities: Independently lead and perform
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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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environments. Experience with parallel computing environments, HPC in a Linux environment. Experience with surrogate modeling. Experience with data analytics techniques. Familiarity with C++ and GPU programming
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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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Requisition Id 15813 Overview: We are seeking a highly motivated postdoctoral researcher with a strong background in sensor integration, data acquisition, and in situ process monitoring