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@ornl.gov This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired. We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich
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to apply due to a disability, please email: ORNLRecruiting@ornl.gov. This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired. We
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, work together, and measure success. Basic Qualifications: A PhD in Materials Science & Engineering, Computational Sciences, Physics, or a related field completed within the last 5 years Demonstrated
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: ORNLRecruiting@ornl.gov. This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired. We accept Word (.doc, .docx), Adobe (unsecured .pdf
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, Materials Science, Engineering Mechanics, Manufacturing Engineering, Mechanical Engineering, Artificial Intelligence/Machine Learning, or a related field completed within the last 5 years Preferred
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an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or
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the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov This position will remain open for a minimum of 5 days after which it will close when
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: https://www.ornl.gov/content/research-integrity Basic Qualifications: To be eligible you must have completed a PhD in chemistry, physics, engineering, or a related field with in the last 5 years
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-flows. Basic Qualifications: PhD in mathematics, computer science, engineering, or related field earned within the last 5 years. Preferred Qualifications: Experience with mesh generation/CFD applications
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transformative solutions to compelling problems in energy and security. Our diverse capabilities span a broad range of scientific and engineering disciplines, enabling the laboratory to explore fundamental science