80 post-doc-computer-graphics Postdoctoral positions at Oak Ridge National Laboratory
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quality program requirements Maintain strong commitment to the implementation and perpetuation of values and ethics Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core
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, health and quality program requirements Maintain strong dedication to the implementation and perpetuation of values and ethics Deliver ORNL’s mission by aligning behaviors, priorities, and interactions
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communication and program management skills are required. This position resides in the Carbon Fiber Technology Facility (CFTF) and the work is performed at the Manufacturing Demonstration Facility (MDF) in
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Engineer will conduct R&D in nuclear nonproliferation with expertise in computational nuclear reactor physics through modeling and simulation (M&S). The candidate will perform analysis and methods
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Requisition Id 16889 Overview: The National Center for Computational Sciences (NCCS) provides state-of-the-art computational and data science infrastructure for technical and scientific
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(PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation. To obtain
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specialists in organic and inorganic synthesis, coordination chemistry, thermodynamics, laser spectroscopy, materials characterization, chemical separations, computational chemistry, and nuclear chemistry. Our
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related field completed within the last 5 years. Experience utilizing computational thermodynamic (CALPHAD) software, such as Thermo-Calc, DICTRA, PANDAT, or FactSage. Proficiency in materials data
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separation science and technologies for energy applications. Support research and program-development activities in advanced separation and purification, including the recovery of critical materials used in
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computational foundations of that capability and help bridge the gap between Bayes theory and practical application: knowledge integration, developing robust likelihood frameworks, sampler behavior for long