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The Center for Nanoscale Materials (CNM) and the Materials Science Division (MSD) at Argonne National Laboratory are jointly seeking a highly motivated postdoctoral researcher to advance quantum
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studies (e.g., EELS, EDS) to probe defect structures and dynamics Apply advanced image processing and analysis; develop AI/ML workflows for quantitative defect characterization Implement high-throughput and
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dynamics. This position focuses on advancing fundamental understanding of light-matter interactions with direct relevance to energy conversion. The research involves exploring the excited-state dynamics and
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structural models and compute electronic and vibrational properties. Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations
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candidate will lead efforts in materials synthesis, in situ/operando characterization, and catalytic performance evaluation. This role offers a unique opportunity to leverage CNM’s advanced characterization
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total X-ray scattering (TXS) and pair distribution function (PDF) analysis capabilities and methodology to study laser-driven structural dynamics in functional materials. This position is part of a
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models for composites of arbitrary structures to predict their homogenized properties. The candidate will also work closely with AI experts to develop workflows for composite structure discovery given
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aims to revolutionize the development of therapeutic platforms for IDPs, creating significant advancements in cancer research and treatment strategies. As part of a collaborative initiative with the
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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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for application to molten salt reactors, pyrochemical treatment of used nuclear fuel, and innovative applications in advanced nuclear systems being developed to meet the national energy needs. As a part of this