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unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In
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simulation and flood inundation modeling. River basin planning and operations modeling, including reservoir simulation and optimization. Hydrodynamic modeling of water temperature and quality constituents
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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
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and image data processing. Specific knowledge related to neural network design, training, and optimization is required. You will be joining a group with core expertise in sensor data analytics from
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supports the design, performance optimization, and reliability of gas centrifuges used in the processing of uranium and stable isotope compounds. Within this organization, the Distinguished Rotor Dynamics
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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, and optimize preprocessing pipelines using HPC resources, targeting scalable execution and automation. Collaborate with domain scientists to integrate pipelines into end-to-end AI workflows specific
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seeking to fill a Postdoctoral Research Associate position to work in the areas of environmental life cycle assessment (LCA), technoeconomic optimization; and industrial energy efficiency and production
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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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, classification, and interpolation of pixel detector data. Exploration of spike-based data encoding/decoding strategies. Hyperparameter optimization using advanced computing resources (e.g., HPC clusters). Detector