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algorithms and parallel/distributed variational algorithms in AI/ML for application workflows and large-scale HPC and QC systems Develop quantum machine learning (QML) algorithms for optimization of multi
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sparse algorithms. The successful candidate will contribute to advancing secure, trustworthy, and efficient AI solutions for scientific applications. Key responsibilities include developing state
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teams to codesign hardware, algorithms, benchmarks and software for QHPC systems, aiming to advance our strategic goals in leveraging quantum computing and high-performance computing (HPC) to develop
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and Electronics group in the Electrification Section of EEID/ ESTD, at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop and deploy algorithmic tools for monitoring
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on the development of new algorithms and methods that can be used to analyze large and complex scientific data using novel computer architectures such as high performance, neuromorphic, and quantum computing. We are a
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conditions, identification of vulnerabilities, and development of resilience enhancement strategies. Contribute to the design, development, and implementation of new models, methods, and algorithms
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discovery with a strong emphasis on domain-driven impact. Develop, optimize, and transition algorithm prototypes to robust implementations Work with ORNL researchers, as well as internal and external project
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field. Expertise in systems dynamics and controls, automation, and/or robotics Demonstrated experience in developing and implementing advanced controls and sensing algorithms Demonstrated ability to work
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join the Data Science and Engineering for Nonproliferation group, where the selected candidate will focus on developing novel, physics-informed data-driven methodologies and apply groung-breaking machine
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embedded controllers. Experience in evaluating converter topologies, developing control algorithms, and writing controller code is expected. Major Duties/Responsibilities: Conduct R&D projects and help