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record of productive and creative research as demonstrated by publications in peer-reviewed journals, patents or commercial products. Excellent written and oral communication skills and the ability
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for this candidate are between two larger efforts in the laboratory. The first effort is in identification of cost-effective technologies (both emerging and at industrial scale) for critical minerals recycling from
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models of gas transport and process behavior in industrial systems Collaborate with a team of scientists from across the national laboratory complex on modeling efforts Extend process flow modeling across
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Requisition Id 17011 Overview: The Nuclear Energy and Fuel Cycle Division (NEFCD) of Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to assist in the development
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sciences to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut
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publishing high-quality scientific results in peer-reviewed conferences and/or journals, with strong written and oral communication skills. Preferred Qualifications: Experience developing system-level or
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backed by demonstrated recent and relevant research and development in the field is a fundamental requirement of this position. Experience with neutron transport and reactor analysis software (SCALE code
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of irradiated ceramics and alloys for tritium technology development using advanced experimental and computational methods. The researcher will perform characterization of model systems using techniques such as
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Postdoctoral Research Associate - Multifunctional Equipment Integration Energy Conversion Technology
system technologies. This position resides in the Multifunctional Equipment Integration Group in the Thermal System Science Research Section, Buildings and Transportation Science Division, Energy Science
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multidisciplinary team. Excellent interpersonal, oral, and written communication skills. Preferred Qualifications: Experience with AI/ML approaches for spatiotemporal or Earth system data, including generative AI