80 electrical-machine-design-"https:"-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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. in Quantum computing, Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a closely related discipline, with demonstrated knowledge of or research experience in
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candidate will support research and development projects that advance the state of the art in machining science, machine tool design and characterization, manufacturing process optimization, and digital
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Requisition Id 16723 Overview: We are seeking a Postdoctoral Research Associate with expertise in artificial intelligence (AI) and machine learning (ML) for multiscale physical systems
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system
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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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. To conduct this work, the successful candidate will use the world's first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric grid analytics, and
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. Represent ORNL and the Learning Systems Group by giving talks at public forums (conferences, workshops, guest lectures, etc.). Basic Requirements: Ph.D. in Computer Engineering, Electrical Engineering
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artificial intelligence for science, knowledge-guided machine learning, and scalable scientific AI workflows. The successful candidate will conduct research at the intersection of machine learning, high
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, irradiation experiments, and rapid design/fabrication. As part of the research team, you will investigate optical fiber instrumentation. More specifically, this position would develop Fabry-Perot interferometer
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Demonstrated experience in control theory and control system design (e.g., model predictive control, feedback control, adaptive control) Experience applying machine learning/AI to engineering systems Proficiency