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optimization schemes. From developing AI models to uncover structure-function relationships with limited data sets, to building automated electrode-electrolyte interface discovery workflows and implementing full
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and unravel structure-function relationships. This position is suited for a highly energetic and self-driven researcher willing to work in highly collaborative teams. This position will involve a
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recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Computational Materials Science, Chemical Engineering or a closely related field. 2. Technical Expertise
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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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phonons, magnons, and other emergent quasiparticles. The successful candidate will lead time-resolved X-ray diffraction experiments to reveal structural and electronic dynamics in condensed matter systems
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Extraction), jointly led by the Chemical Sciences and Engineering (CSE) and Applied Materials (AMD) Divisions at Argonne National Laboratory. This project focuses on understanding the evolution of structure
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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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information science and light–matter engineering, while engaging with CNM’s cleanroom and characterization capabilities, APS ultrafast and nanoprobe X-ray beamlines, MSD’s THz initiatives, and Q-NEXT’s national quantum
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The Chemical Sciences and Engineering Division is seeking a highly qualified and motivated postdoctoral researcher to join our team in the area of light-matter interactions, with a particular focus
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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