359 computer-science-intern "https:" "https:" "https:" "European Commission" positions at Oak Ridge National Laboratory
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Qualifications: An MS in computer science, mathematics, or a related field completed within the last 5 years. A BS degree and at least 2 years of relevant research experience will also be considered. Familiarity
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at Oak Ridge National Laboratory (ORNL). This position resides in the Materials Theory Group in the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at ORNL. Major
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an ongoing random drug testing program. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing
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empirically informed methods to advance the fundamental engineering understanding of gas centrifuge systems. The group leverages analytical techniques and advanced computational tools—including finite element
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manufacturing for applications in aerospace, automotive, and marine/shipbuilding industries, as well as trending areas of international composite research in material science, mechanical engineering, chemical
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workplace – in how we treat one another, work together, and measure success. Basic Qualifications: BS in Industrial Controls, Electrical or Electronics Engineering, Automation Technology, Computer Networking
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Requisition Id 15764 Purpose The Glenn T. Seaborg Initiative (GTSI) of Oak Ridge National Laboratory (ORNL) is committed to enhancing and maintaining US capabilities in actinide science and
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of policies, practices, and procedures. Ensure technical compliance with 10 CFR 830 Subparts A and B affecting facility safety through implementation of ORNL Standards Based Management Systems and internal
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be a part of the Counterintelligence (CI) team responsible for managing and implementing the Cl Program that encompasses all contractor facilities at Oak Ridge, TN; Portsmouth, OH; and Paducah, KY. We
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Informatics portfolio. You will be expected to work with a team as well as independently research and develop AI-driven methods to enhance discovery and usability of Atmospheric Radiation Measurement (ARM) data