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challenges, and scientific data workflows Preferred Qualifications: An active Q/SCI clearance Ph.D. in Information Science Excellent written and oral communication skills Ability to work independently and to
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Requisition Id 16315 Overview: We are seeking an engineer who will focus on using surveying and engineering analysis skills to plan accurate, high-precision metrology and alignment on a wide variety
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. The Oak Ridge National Laboratory (ORNL) is one of the nation’s largest multi-program science and technology laboratories within the U.S. Department of Energy (DOE). The Enrichment Science and Engineering
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Qualifications: Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field Strong programming skills in C++, Python, or similar scientific computing
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, and testing of complex systems. Familiarity with engineering codes and standards (e.g., ASME, AWS, AGS, DOE) Familiarity with nuclear quality requirements such as ASME NQA-1 Excellent written and oral communication
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order to maintain conformance to both program and contractual requirements. Reviews and interprets government and ORNL procurement policies, regulations and procedures. Deliver ORNL’s mission by aligning
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challenging and impactful research and development programs in healthcare informatics, bioinformatics, high performance computing and deep learning. We have a collaborative environment focusing on designing
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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 laboratory, ORNL has
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Computational Sciences Directorate, with an emphasis on purchase of high-performance computing (HPC) systems, contracts for research & development, as well as software and software-as-a-service subscription
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science, electrical engineering, computer engineering, computer science, data science, applied mathematics, or a closely related field Demonstrated experience applying data analytics, statistical modeling