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advance the design and operation of next-generation thermal systems, developing strategies to model, optimize, predict, and autonomously control thermal systems behavior in complex systems. The candidate
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model selection and comparison. Experience contributing to open-source scientific software, including version control, testing, continuous integration, documentation, and code review. Knowledge of
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in Multiphysics modeling software (ANSYS, COMSOL, MOOSE, etc.) to model materials in high temperature or high stress conditions. Experience working with high pressure systems and pressure control
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Model, working closely with the experimental team to understand this device’s PMI physics and optimize performance of the device in its upcoming campaigns. The position resides in the Power Exhaust and
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trait databases TRY, FRED, LeafWeb, Sapfluxnet, PSInet) to translate trait variation into model parameter priors and functional constraints, and to explore parameter relationships with environmental
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ecosystem processes. The position offers the opportunity to work at the interface of model development, observational data synthesis, and emerging AI/ML methods, in close collaboration with researchers from
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), and 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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, characterization of isotopic content of nuclear materials, and detector response to radiation sources. Model conceptual advanced reactors and their subsystems. Evaluate safeguards metrics during
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workflows. Major Duties/Responsibilities: Participate in the design, implementation, and deployment of scalable AI/DL models for power grid systems, including surrogate models and foundation-model workflows
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tensor network algorithm development and application. Competency with common scientific programming languages such as C++, Python, and/or Julia and version control systems. Experience in parallel