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sensing, quantum information science, superconducting circuit, or magnonics. Proficiency in scientific software development (e.g., Python, COMSOL, HFSS or similar languages). Ability to model Argonne’s core
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and characterizing new materials and membranes for critical minerals separations. The ideal candidate will have expertise in membrane development and electrochemical processes. This position will be
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have a strong background in fundamental electrochemistry, with preferable hands-on expertise in computational materials science. The applicant should be well versed in code development, application of AI
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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photonic platforms through nano- and meso-scale lithographic fabrication. This position supports two complementary, three-year Laboratory Directed Research and Development (LDRD) projects focused on hybrid