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compatible with the leadership-class high-performance computing facilities available at ORNL and other DOE facilities. Independently plan and conduct simulations while routinely adapting them to integrate with
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sciences, and high-performance computing. The candidate will have opportunities to work with world-class computing resources, including ORNL’s leadership-class computing ecosystem, and to contribute to AI
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mechanical testing. This knowledge will be used to assess the suitability of these materials for nuclear and space applications. This position resides in the Materials Processing Group within the Materials
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. This researcher will focus on advancing secure, trustworthy, and efficient AI solutions for scientific applications by developing state-of-the-art sparse algorithms in matrices, tensors, and networks
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. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top
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Requirements: Applicants cannot have received their PhD more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length
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to accomplish multiple tasks within deadlines, and adapt to ever changing needs. Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must
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, reactor core, spent fuel, and fuel cycle applications through leadership in the development and analysis of SCALE and/or the Virtual Environment for Reactor Applications (VERA) simulations and in
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the last 5 years. Preferred Qualifications: Proven RDD&D experience in urban-scale building energy modeling. Experience planning and designing solutions for a variety of community projects, including
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more than five years before application; all degree requirements must be completed before the appointment begins. Hands-on research experience building, aligning, or characterizing optical systems