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(ORNL). Multiple positions are available to support R&D with different research focuses. They include innovations in joining and materials processing/synthesis, AI/ML for process monitoring and control
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Requisition Id 16093 Overview: Oak Ridge National Lab is seeking a Postdoctoral Research Associate to advance quantitative, high‑throughput neutron imaging for next‑generation energy‑storage
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Program (DOE IP) to advance the chemical processing of unique f-element isotopes, including Cf-252, Bk-249, Es-254, Fm-257, and Pm-147. A core focus of the DOE IP is to improve and develop novel chemical
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, pyrometry, spectroscopy, co-axial and off-axis high speed imaging, and more) for process monitoring and diagnostics. Develop and implement data acquisition, signal processing, and data analytics frameworks
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research will involve Python scripting within the Thermo Fisher AutoScript environment to control operation of the microscope beam, stage, detectors, and spectrometers, with a particular emphasis on annular
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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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compliance, reproducibility, and interoperability across scientific domains. By improving data readiness processes, this role will amplify the potential of AI-driven discovery in areas such as high energy
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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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physical characterization techniques (differential scanning calorimetry, dynamic light scattering, small angle neutron and/or x-ray scattering) to characterize the DIBs; and (3) Develop/implement image
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and machine-learning-driven optimization frameworks for polymer composite manufacturing processes. This position resides in the Composites Innovation Group in the Manufacturing Science Division (MSD