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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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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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science for quantum information hardware with the industrially mature solid state platforms of silicon/silicon germanium and silicon carbide spin qubits. The position will focus on heterogeneous integration
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spectroscopy (e.g., transient absorption), including laser operation, optical alignment, and data analysis Experience in synthetic inorganic chemistry and transition metal complex photophysics Job Family
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The Materials Science Division (MSD) at Argonne National Laboratory is seeking a postdoctoral appointee to join the Nanoscale Magnetic and Electronic Heterostructures group. This position will focus
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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
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The Data Science and Learning Division (DSL) at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting edge molecular and microbiology work to enhance non-proliferation
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ionomer materials. Position Requirements Ph.D. completed in the past 5 years or soon-to-be-completed in chemistry, chemical engineering, materials science, or a closely related field. Strong background in
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to assess evolving risks in coastal-urban regions. Other key responsibilities include: Mesh design and high-resolution data utilization. Develop and refine high-resolution barotropic ocean meshes along U.S
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The Data Science and Learning Division (DSL) of the Computing, Environment and Life Sciences Directorate (CELS) and the Materials Science Division (MSD) of the Physical Sciences and Engineering