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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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(HPC). The postdoc will work closely with visualization researchers, AI scientists, and domain application teams across Argonne and the broader DOE ecosystem. The goal of this postdoctoral position is to
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staff scientists, engineers, postdocs, and students, with an active research portfolio that spans: Leading electron-scattering experiments at Jefferson Lab (CLAS12, SoLID, Hall A, B, and C) Major
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staff members, two engineers, and postdocs and students. Our program spans electron-scattering experiments at Jefferson Lab in Hall A, B, and C, including CLAS12 and SoLID. We have led SeaQuest and are
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quantum transduction and terahertz (THz) photon generation via enhanced light–matter interactions. The postdoc will lead efforts in device patterning and the integration of complex materials—such as
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undergraduates. Postdocs benefit from strong interactions with experts in applied mathematics, computer science, device physics, materials science, and statistics, as well as access to world-leading supercomputing
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contribute to the Lab’s broader effort in conversion and separation of carbon-based materials. The role will require the individual to work with personnel that perform machine learning and molecular
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preservation (e.g., glycerol stocks, subculturing), aseptic technique, and operation under BSL-1 and BSL-2 containment requirements. Experience with microbial molecular biology techniques, including DNA/RNA
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four staff members [Ian Cloët, Alessandro Lovato, Anna McCoy, and Yong Zhao] and several postdocs and students. The group has a broad research program in QCD/hadron physics and nuclear structure
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) of electrochemical energy storage devices (diagnosis) and predict the SOH into the future (prognosis). The primary projects this postdoc will contribute to relate to lithium-ion batteries, advanced lead-acid batteries