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. Implement and optimize data representations and pipelines suitable for machine learning and uncertainty quantification. Collaborate with AI/ML experts to design and test inference methods that map
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advanced many-body methods, high-performance computing, and machine learning approaches. The successful candidate will play a leading role in developing computational methods and high-performance algorithms
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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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optical systems, thermal imaging, pyrometry, spectroscopy, high speed imaging or acoustic sensing. Familiarity with data analytics, machine learning, or signal processing. Knowledge of metal additive
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research, operations, and community engagement, and work cooperatively to leverage scientific capabilities across ORNL. Work in a highly collaborative environment with data scientists, machine learning
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analytics that enhance and evolve business operations and scientific decision-making capability and related activities at ORNL.Qualified applicants will have a solid foundation of Generative AI and Machine
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injection techniques, space charge simulation and theory, and control and mitigation of beam halo and other beam loss mechanisms, and machine learning efforts. Provide leadership to the group to support safe
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of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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to DOE sponsors, industrial partners, and international collaborators. Basic Qualifications: PhD in Computer Science, Computer Engineering, or a field closely related to the job duties of this position. A