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data-model integration, leveraging the U.S. Department of Energy’s (DOE) Leadership-Class Computing Facilities to advance predictive understanding of complex environmental systems. Major Duties
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superconducting behavior, utilizing NV centers in diamond and spin defects in 2D materials in variable-magnetic-field cryogenic environments. The candidate will leverage single- and ensemble-spin based sensors
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species. It can be fine-tuned for downstream applications such as predicting genetic perturbations, optimizing photosynthetic apparatus for performance, selecting top performing genotypes for various
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strategies. Major Duties/Responsibilities: The selected candidate will have responsibility for: AI Model Development: Design, develop, and apply innovative AI models to analyze and predict the response
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the goal is to build scalable, semi-automated, human-in-the-loop AI solutions for DOE and national infrastructure. Focus areas include hazard identification, predictive risk analysis, incident trend
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Duties/Responsibilities: Develop and operate Control Room software for SNS accelerator tuning and monitoring. Conduct beam studies on the SNS beam to calibrate simulations and validate predictions. Develop
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and optimize molten salt thermophysical property measurements, develop and utilize theoretical models and frameworks to predict salt properties, molten salt thermophysical property database expansion