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Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate who will support the areas of multimodal imaging, AI architecture, and efficient
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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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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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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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). NCCS operates the Frontier exascale supercomputer and world-class data facilities. This role sits at the intersection of AI at scale and HPC, giving you unmatched resources to prototype new ideas, run
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twins are leveraged to develop paradigm shifts in quality assurance, quality control, real-time process control, and design optimization for the United States. In this digital environment, you will use
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dynamic instabilities in materials; development of a polarization-based correlation chopper prototype; simulation of instrumentation using McStas; analytics of materials structure and dynamics using neutron
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measure success. Basic Qualifications: A PhD in Materials Science and Engineering or a related field completed within the last 5 years Preferred Qualifications: Strong background in computational and image
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their appointment. Preferred Qualifications: Experience with pan-genome datasets. Experience in plant stress/growth physiology and phenotyping, including extraction of relevant traits from image-based platforms