52 electric-machine-"https:" "https:" "https:" "https:" "https:" Postdoctoral positions at Oak Ridge National Laboratory
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– in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in physics, optics, photonics, applied physics, electrical engineering, or a related discipline, earned no
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, and measure success. Basic Qualifications: PhD in Plasma Physics, Electrical Engineering, Nuclear Engineering, or a closely related field completed within the last 5 years, or expect to complete a PhD
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photonic quantum sensing and computing. Experience with control electronics, data acquisition systems, machine learning and AI for control and optimization of experimental apparatus. Experience with vacuum
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responses to current or imposed environmental conditions. Research may leverage: Laboratory, growth chamber and field experimental data, and/or new measurements to quantify molecular to ecosystem scale
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of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing. Author peer reviewed papers for internal and external release as
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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Requisition Id 16802 Overview: We are seeking a Postdoctoral Research Associate for the development and application of advanced multiphysics simulations, and machine learning (ML) methods relevant
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral
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Postdoctoral Research Associate - Multifunctional Equipment Integration Energy Conversion Technology
in mechanical, chemical, materials, or electrical engineering, or a related discipline obtained within the last five years. A minimum of 3 years of experience in (a) design and operation of
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machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model development. Complete simulation verification, model validation, uncertainty quantification, and documentation