301 computational-physics-"https:"-"https:"-"https:"-"https:"-"IFM" positions at Oak Ridge National Laboratory
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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 of addressing the nation’s
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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 of addressing the nation’s
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to accomplish multiple tasks within deadlines, and adapt to ever changing needs Special Requirements: Physical Requirements: Work involves various physical requirements and working conditions. As such, a pre-hire
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. Preferred Qualifications: Education or experience that includes a technical field such as engineering, chemistry, physics, computational sciences, or a technical degree is helpful. An advanced degree and
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will focus on long-term annual capacity planning to meet program objectives as well as short-term machine operations planning based on resource availability and changing operational conditions. This
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: Physical Requirements: Work involves various physical requirements and working conditions. As such, a pre-hire physical will be required after offer. Q or L clearance: This position requires the ability
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Requisition Id 15649 Overview: We are seeking a Quality Representative (QR) who will focus on implementing Quality program requirements in support of Research and Development (R&D) within
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, health, and quality program requirements. Coordinate project meetings and documentation including Activity Hazard Analyses, work permits, requests for information, submittals, and scope changes between
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Computational/theoretical chemistry and/or physics, chemical engineering, materials or a closely related field completed within the last 5 years. Preferred Qualifications: Experience with coding, electronic
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Sensing Group (RSG). RSG is part of the Oak Ridge National Laboratory (ORNL) and seeks to hire qualified candidates to support photogrammetry and 3D computer vision research initiatives with emphasis