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advanced techniques Plan and execute research on battery materials using structural, chemical, mechanical, and electrochemical methods Maintain adherence to all Laboratory and Divisional Environmental
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algorithms to develop cybersecurity, optimization, and control solutions for real-world grid applications. Candidates will be required to work in at least 4 of the following areas: Build, simulate, and
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, modeling and analysis, integrating diverse data sets to identify global risks affecting sourcing strategies. In this role you will: Conduct and contribute to research and model development to enhance
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is expected to support and advance the on-going research program of the Fundamental Symmetries Group and to develop an innovative research plan to further enhance the reach of experimental fundamental
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activities to disseminate knowledge and raise awareness. Contribute to the development of a strategic research plan for industrial and building decarbonization aligned with multiple DOE Offices in
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will conduct Research and Development to help develop processes for the economic production of critical and rare earth metals. Perform technical work related to the development of new processes
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instrument programming. Interest in software development, in particular, expertise in C or C++ and Linux/Unix programming and Python. Familiarity with scientific productivity, as demonstrated by publications
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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-sponsored projects that would entail developing analysis insights critical to strategic technology RDD&D investments at the federal and state levels. Such analyses would be rooted in transparent, repeatable
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on convective systems and precipitation. Key responsibilities include conducting high-resolution model simulations, contributing to model development, analyzing both model results and observational datasets, and