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(ORNL). As a postdoctoral fellow, you will produce publishable results at a steady pace and work at the interface of neutron imaging, computational modeling, and workflow automation. Applicants with
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Ph.D degree in electrical engineering, computer engineering, computer science, or a related discipline Demonstrated experience developing, training, and applying AI algorithms to physical sensor data
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demonstration of centrifuge technology. The successful candidate will participate in research and development (R&D) activities that strategically advance science and technology focused on gas testing of prototype
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.) to enable real-time process monitoring of the Directed Energy Deposition (DED) printing process. A background in sensors, instrumentation, and data analytics is preferred. Strong communication and program
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technology focused on gas testing of prototype enrichment devices for processing uranium-bearing and stable isotope compounds. The Mechanical Systems Modeling Group applies first-principles physics and
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Requisition Id 15815 Overview: The Workflows and Ecosystem Services (WES) group under the Advanced Technology Section (ATS) of the National Center for Computational Sciences (NCCS) is seeking a
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, substation, corridor scenarios) Integrate physics-informed machine learning models with signal processing feature extraction Develop prototype software tools for automated waveform analytics and real-time
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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-resolution microscopy, and in situ neutron or X-ray scattering and tomography methods. Strong background in computational and image-processing software, scientific programming, and high-performance computing
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technology. The successful candidate will provide research and development (R&D) leadership to the group that strategically advances science and technology focused on gas testing of prototype enrichment