54 medical-image-processing-phd-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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vision transformer or large vision AI model Expertise in high performance computing Expertise in image and spatiotemporal data processing Expertise in federated learning on large computing clusters A
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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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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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Director's office can be found here: https://www.ornl.gov/content/research-integrity . Basic Qualifications: A PhD in physics, chemistry, biochemistry or a related field completed within the last five years
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to ORNL's Research Code of Conduct. Our full code of conduct and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity . Basic Qualifications: PhD in
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD degree in Computer Science or related discipline. Demonstrated
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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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collaboration within a multi-disciplinary research environment consisting of mathematicians, computational and computer scientists, and domain scientists conducting basic and applied research in support of ORNL’s
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characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Design and evaluation of approaches for time-sensitive or data-intensive processing of data originating