70 gaussian-process-regression Postdoctoral positions at Oak Ridge National Laboratory
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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materials within the uranium fuel cycle. Research topic areas will be related to understanding the effects of material processing on chemical and physical observables and translating this understanding
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, and processing of materials under high temperature pyrolysis. The candidate will aid staff in conducting high quality research by developing, integrating, and deploying materials to be used
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architectural models, system-level simulators, and performance modeling frameworks for QHPC systems, capturing relevant characteristics of quantum processing units, classical HPC resources, interconnects, system
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a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD degree in materials science, nuclear, or mechanical engineering, or a related
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Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: Candidates must have a PhD in nuclear
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characterization of polymers to maximize material performance but also close collaboration with multidisciplinary teams to scale up manufacturing processes for high-performance fibers. A key aspect involves
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and functionalized sorbents for the selective extraction and recovery of gallium (Ga), germanium (Ge), and other critical minerals from complex zinc-processing feedstocks. The successful candidate will
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fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, computer science, or a related field completed within
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for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically