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will contribute to developing and improving the performance of next-generation thermal systems—including HVAC, water heating, and data center cooling—at both the system and component level. This
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molecular dynamics simulations. Develop and optimize automated workflows for data generation and active learning , including molecular dynamics (MD) sampling, configuration selection, labeling with
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, uncertainty quantification, and documentation. Optimize system and component designs for performance and safety. Develop agentic workflows for scientific computing. Author peer-reviewed papers, technical
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land component (ELM) and its peatland-specific configuration (ELM-Peatlands), with a focus on improving the representation of nutrient cycling dynamics and their coupling to hydrological and
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, synchronous generators, large loads, transmission networks, etc. Develop simulation algorithms that enable large-scale simulations. Integrate (or co-simulate) grid component/device models into open-source
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-solving, conduct experimental campaigns, perform materials synthesis and analysis, sub-component fabrication, process optimization and integration, and prepare technical documents and research
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expertise in multi-physics FE simulations is preferred. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or
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expertise in multi-physics FE simulations is preferred. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process