261 data-"https:" "https:" "https:" "https:" "U.S" uni jobs at Oak Ridge National Laboratory
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, collaborative relationships with diverse stakeholders. Proficiency in applicant tracking systems (ATS), recruitment platforms, and data analytics tools. Comprehensive knowledge of employment laws, regulations
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can lead computational and experimental activities using commercial codes to compare with experiments and also be able to develop new computational models and computer programs. The successful candidate
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environment. 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
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technical leadership in AI security evaluation mechanisms. Required Qualifications Master’s Degree in Computer Science, Computer Engineering, Cybersecurity, or related fields with 7-10 years of experience
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economic benefits for the nation. Our partnerships with U.S. Department of Energy (DOE) laboratories, universities, and industry enable us to accelerate science and innovation. The Office of Research
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transformations as they relate to microelectronics, quantum materials, quantum information systems and autonomous synthesis in support of ORNL’s “atoms to applications” strategic initiative. As part of the CNMS
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Requisition Id 15574 Overview: 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
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of abnormal events or equipment issues. Monitor system performance, review maintenance and reliability data, and help identify equipment or system vulnerabilities. Follow environmental, safety, health, and
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enforced. All team members deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. As a U.S. Department of Energy
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radiological protection expertise for work planning and radiological design and control. Work with NRPD and applicable line management to monitor radiological performance, evaluate data, and develop performance