54 channel-coding-electrical-engineering Postdoctoral positions at Oak Ridge National Laboratory in United States
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experiments to neutron reflectometry studies. The main objectives are: (1) To implement fluorescence microscopy techniques and Flicker spectroscopy to studies of DIBs under electrical stimulation; (2) Use other
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challenges facing the nation. The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral
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of advanced materials. Research efforts will include the application of density functional theory packages and in-house codes, and the development of supplemental numerical tools, to describe
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another, work together, and measure success. Basic Qualifications: A Ph.D. degree in electrical engineering, or related discipline completed within the last five years. Expertise in power systems and power
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Computational/theoretical chemistry and/or physics, chemical engineering, materials or a closely related field completed within the last 5 years. Preferred Qualifications: Experience with coding, electronic
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qubit engineering to quantum algorithmic analysis to applications across the physical sciences (condensed-matter or high energy physics, data science). You will Interpret, report, and present research
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production target materials. This involves the development of experimental plans to examine material properties such as thermal diffusivity, thermal conductivity, and thermal expansion – material properties
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Design Group in the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL). This position lives in the Alloy Behavior and Design Group
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. in Hydrology, Earth system science, Water resources engineering, Computational sciences, Computer sciences or a related field completed within the last 5 years (or expected soon). Demonstrated
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environment. The successful candidate will develop and apply advanced machine learning techniques—including multimodal AI, computer vision, and large language models—to complex scientific and engineering