83 web-programmer-developer "https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral research jobs at Argonne
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The Chemical and Fuel Cycle Technologies division is seeking a Postdoctoral Appointee to join a multidisciplinary team developing processes to support molten salt reactor (MSRs) fuel cycles
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The Energy Systems and Infrastructure Assessment (ESIA) division provides the rationale for decision makers to improve energy efficiency. We develop and use analytic tools to help the U.S. achieve
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the domains of environmental, water, and energy system analysis. Prepares reports, papers, and presentations for conferences, workshops, and technical journals. Supports program development including
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2.0) program. The collaboration team includes Clarence Chang, Tim Hobbs, Dafei Jin, Yi Li, Marharyta Lisovenko, Valentine Novosad, Zain Saleem, Tanner Trickle, and Gensheng Wang. We seek highly
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This position will be dedicated to research projects aiming developing and implementing experimental focused application of AI and automation tools for unraveling fundamental interfacial processes
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define requirements and performance specifications for future HEP/NP detector systems Perform detector concept development, system-level design, and optimization leveraging emerging computing architectures
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increasing independence in defining research problems, developing methodologies, and driving publications. The role values strong research judgment and analytical thinking, complemented by effective use
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on understanding novel and emergent behavior in nanoscale magnetic heterostructures, particularly in confined 2D van der Waals magnets and related devices. The goal of the program is to study and control magnetic
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contribute to research and model development to enhance the resilience of domestic and global supply chains for clean energy technologies. Lead technical and policy analysis to inform decision-makers
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. Working within an interdisciplinary team, you will develop frameworks that connect atomistic features, mesoscale dynamics, and device-level performance. The effort will integrate heterogeneous data from