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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL
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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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a unique opportunity to develop cutting-edge high-performance computing (HPC) that incorporate machine learning/artificial intelligence (ML/AI) techniques into visualizations, enhancing the efficiency
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intelligence (ML/AI) techniques that incorporate uncertainty into visualizations, enhancing the efficiency and reliability of scientific discovery. It also offers exciting prospects for direct collaboration with
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Requisition Id 15764 Purpose The Glenn T. Seaborg Initiative (GTSI) of Oak Ridge National Laboratory (ORNL) is committed to enhancing and maintaining US capabilities in actinide science and
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to the development of scalable, explainable, and uncertainty-aware AI methods that enhance model robustness, reliability, and scientific discovery. Publish research findings in high-impact journals and present results
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manufacturing technologies and manufacturing systems that could achieve transformative gains in process productivity and enhance manufacturing sustainability Strong analytical capabilities with an experience in
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materials that may serve as model systems displaying quantum behaviors. It will also provide opportunities for collaboration with quantum computing efforts within the Quantum Science Center, guiding and
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(e.g., deep learning, implicit neural representations, diffusion models) for CT reconstruction, enhancement, and defect detection. Advance algorithms for multi-modal tomography (X-ray, neutron, electron