50 phd-image-processing-"Fraunhofer-Gesellschaft" Postdoctoral positions at Oak Ridge National Laboratory
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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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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 Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD in Materials Science and
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by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in physics or a related field completed within the last 5 years
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Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD
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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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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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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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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