350 computer-programmer-"https:"-"CNR" "https:" "https:" "https:" "https:" "U.S" "U.S" positions at Oak Ridge National Laboratory in United States
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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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positions require passing a pre-placement drug test and participation in an ongoing random drug testing program. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL
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companies participating in the DOE’s Better Plants program. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service
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program Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a
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test and participation in 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
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to address scientific and engineering problems, collaborate with leaders in your field and across the laboratory, while working with the world’s fastest computers, and disseminate innovative results through
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, reliable, predictable, and efficient operations. This scope includes the HFIR maintenance program and processes; implementation of corrective, predictive, preventative, and modification work activities; work
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the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once
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deadlines, and adapt to ever changing needs. Special Requirements: HSPD-12 PIV badge: This position requires the ability to obtain and maintain an HSPD-12 PIV badge. About ORNL: As a U.S. Department of Energy
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across diverse clients. You will use Frontier's computational power to scale and validate these privacy-preserving algorithms, enabling breakthroughs across energy and image modeling domains. You will also