354 computer-programmer-"https:"-"Prof" "https:" "https:" "https:" "https:" "U.S" "U.S" "P" positions at Oak Ridge National Laboratory
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: Experience in real-time simulation hardware like Opal-RT and RTDS. Experience with software development. Experience with use of DSPs, FPGAs, advanced computing (e.g., GPUs, QPUs). Excellent written and oral
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: 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 challenges. Our team is made up of over 7,000
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, engineers, and program managers to gather technical information and translate complex material into accurate, web-optimized formats. Draft and edit web content to ensure clarity, technical accuracy, and
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participation in an ongoing random drug testing program. In addition, due the SCI, you may also be subject to random polygraph testing. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national
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require passing a pre-placement drug test and participation in an ongoing random drug testing program. Visa Sponsorship: Visa sponsorship is not available for this position. About ORNL: As a U.S. Department
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-accepted standards and laboratory and division-level processes and guidelines, you’ll mentor the team and assign, plan, schedule and track tasks. Specific responsibilities of the position include, but
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Code or skill level and estimating the duration of time (i.e. labor) for each task. Create the Bill of Materials (BOM) for the job plan and submits the Materials Request requisition. Write standard work
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culture. Preferred Qualifications: Demonstrated experience engaging with U.S. Department of Energy (DOE) program offices and aligning work with their strategic priorities. Motivated self-starter with
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Program (DOE IP) to advance the chemical processing of unique f-element isotopes, including Cf-252, Bk-249, Es-254, Fm-257, and Pm-147. A core focus of the DOE IP is to improve and develop novel chemical
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Postdoctoral Research Associate in the areas Artificial Intelligence (AI) for Integrated Hydrology Modeling. The successful candidate will have a strong background in computational science, data analysis, and