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scheduled to run in CY26 Lead role in our MCP-PMT R&D program, with emphasis on device characterization and QA You may combine these focus areas with other ongoing projects in our group. About Argonne and the
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to the Lab’s broader effort in CH4 and CO2 utilization R&D. The role will require the individual to work with personnel that perform machine learning and molecular simulations and electrochemical device testing
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detectors while also having flexibility to pursue your own research interests. Research Focus Participate in a detector R&D program aimed at developing superconducting nanowire sensors to enable
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy
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The Postdoctoral Appointee will be part of an R&D group conducting use-inspired research supporting the development of process technologies for next-generation nuclear/chemical/electrochemical
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completed Ph.D. within the last 5 years in Computational Biology, Bioinformatics, Machine Learning, Artificial Intelligence, Virology, or a related field Strong programming skills in Python, R, or Julia, with
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. Familiarity with techno-economic analysis. Experience with scientific programming languages (e.g., R, Python, Java) and statistical software (e.g., Stata). Ability to create visualizations to effectively
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physics, nuclear theory, nuclear data, accelerator R&D and operates the DOE Office of Nuclear Physics National User Facility, the Argonne Tandem-Linac Accelerator System (ATLAS). As an equal employment