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cooling systems Work across system-level and component-level design challenges Integrate predictive and optimization techniques to enhance system efficiency, reliability, and autonomy Design and implement
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using reliable classical reference calculations and extending toward more challenging regimes. As part of our team, you will work closely with ORNL staff and external collaborators in quantum computing
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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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supports the energy reliability and prosperity mission of the Energy Department (DOE) through transformative science and technology solutions, including research supporting the Office of Electricity (OE
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on physical robotic systems. Establish quantitative measures for localization drift, mapping accuracy, and navigation reliability. Publish results in peer-reviewed journals and conference proceedings, and
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relationships between manufacturing intent, machine behavior, and part performance Optimization of manufacturing processes for improved throughput, reliability, and quality You will contribute to the development
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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