52 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Birmingham-Newman-University" positions at Argonne in United States
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Argonne National Laboratory’s Accelerator Science Division is seeking a Postdoctoral Appointee to contribute to the development of a Sub- THz Collinear Structural Wakefield Accelerator
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We are seeking a highly motivated postdoctoral researcher to join the Center for Nanoscale Materials (CNM) at Argonne National Laboratory. The successful candidate will contribute to the development
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to proposal/experiment planning. The postdoc will interface directly with visiting researchers to execute experiments at the beamline, including hands-on support during beamtimes and development of practical
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Development (LDRD) project titled “Development of Tunable and Narrow Bandwidth Terahertz Light Source for Light-Active Quantum Materials.” The successful candidate will lead the design, implementation, and
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artifacts, and developing an independent research agenda in AI for science. Core responsibilities include: Leading research on foundation models, including problem formulation, algorithmic development, and
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. The project will involve development of novel parallel algorithms to facilitate in-situ analyses at-scale for multi-million and multi-billion atom simulations. In this role, you can expect to work on enhancing
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of experimental quantum communication hardware development, optical memory qubit characterization, and fiber-based networking demonstrations using novel memory qubits. The goal is to employ the natural telecom
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Postdoctoral Appointee - Investigation of Electrocatalytic Interfaces with Advanced X-ray Microscopy
, physics-informed AI agent that accelerates discovery in catalysis science—particularly for the CO₂ reduction reaction (CO₂RR) and oxygen evolution reaction (OER). The postdoc will design and perform
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for Microelectronics” —a physics-informed AI framework that links composition, structure, and operating conditions to defect evolution and functional performance. The successful candidates will lead experimental
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of progress in relevant fields and contribute to CNM and the broader user community through method development, best practices, and mentoring Support end-users with high performance computing and workflow needs