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The Theory Group in the Physics Division at Argonne National Laboratory is now seeking candidates for postdoctoral positions in nuclear theory, to begin as early as Spring 2026. The positions
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The position is part of a new collaboration between Argonne National Laboratory, the University of Notre Dame, and UIUC, supported by the Quantum Information Science Enabled Discovery 2.0 (QuantISED 2.0) program. The collaboration team includes Clarence Chang, Tim Hobbs, Dafei Jin, Yi Li,...
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The Particle Theory Group in the High Energy Physics Division at Argonne National Laboratory invites applications for one or more Postdoctoral Research Associate positions in theoretical particle
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. (typically completed within the last 0-5 years) in computer science, applied mathematics, operations research, engineering, economics, or a related quantitative field. Demonstrated expertise in AI, machine
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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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and lanthanides within controlled atmosphere gloveboxes. Apply chemical thermodynamic and kinetic theories to understand processes and develop models of material interactions and behavior in molten salt
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and lanthanides within controlled atmosphere gloveboxes. Apply chemical thermodynamic and kinetic theories to understand processes and develop models of material interactions and behavior in molten salt
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with aspects of condensed matter and BCS superconductivity theory applicable to high kinetic inductance superconducting materials Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type
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findings at scientific conferences. Position Requirements Ph.D. completed within the past 5 years, or soon to be completed, in physics, materials science, chemistry, computer science, applied mathematics
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environmental trade-offs. Contribute to projects involving capacity expansion, production cost modeling, and equilibrium modeling of power systems. Design and apply mathematical optimization models, including