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areas is preferred and will help the candidate succeed: X-ray absorption spectroscopy theory and modelling, and handling large synchrotron/X-ray datasets. Experience with vector databases (e.g. Pinecone
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-detector and synchrotron communities. Maintain a strong commitment to safety, quality, and inclusive teamwork in a dynamic user facility environment. What We Offer The opportunity to help build and lead a
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The Energy Systems and Infrastructure Assessment (ESIA) division provides the rationale for decision makers to improve energy efficiency. We develop and use analytic tools to help the U.S. achieve
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or image processing Experience with AI-assisted or feedback-driven fabrication workflows Interest in quantum photonic platforms, electro-optic systems, or light–matter coupling physics Application Materials
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-driven modeling (including ML/AI where appropriate) to help anticipate vulnerabilities and inform decision-making for energy deployment and national competitiveness. In this role you will : Conduct and
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for electro-optic modeling Desirable Skills Data analysis using Python Experience with autonomous or AI-assisted synthesis workflows Familiarity with quantum transduction or quantum information science
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journal/conference publications; the successful candidate will develop open-source packages and help disseminate research results to academic and industry community; and will draft research proposals and
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coherence studies Background in quantum device design, fabrication, and characterization Familiarity with AI-assisted measurement techniques Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker