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develop correlations to describe the characteristics of materials and models to describe their behavior in typical reactor environments. You will participate in planning, developing, and implementing
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to catalyst/electrolyzer system design, optimization, integrated process modeling, techno-economic analysis, and environmental impact assessments. Additionally, the candidate will prepare reports, presentations
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in modeling, analysis and control of electric power distribution and transmission system, applying state of the art machine learning (ML) and deep learning algorithms to develop cybersecurity
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objectives and performance targets. Develop or modify electrode materials, membranes, or other components to enhance separation performance. Collaborate with multidisciplinary teams to scale electrochemical
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unit operations performed in molten salt electrolytes. As a part of this team, you will: Perform integrated system modeling and data analyses to develop and apply complex flowsheets and process models
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The Low-Energy Nuclear Physics Research Group (LER) of the Physics Division at Argonne National Laboratory seeks outstanding individuals to fill an open postdoctoral position to develop and conduct
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candidate will develop computational models at the mesoscale or macroscale level using the principles of mass, momentum, and energy balance, to describe morphology changes, dendrite growth, side reactions
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Development and applications of the next-generation X-ray nanoprobe The candidate will join a multidisciplinary team to develop the next-generation scanning X-ray nanoprobe with cryogenic
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economic and decarbonization goals. This role will build on existing work at Argonne and collaborate with a multi-disciplinary team and will involve the following: Conduct research and analysis and develop
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contribute to optimization of reactor and fuel cycle design. In this position, the candidate will develop computational methods and/or computer codes to model the physics and engineering of reactor and fuel