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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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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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ecosystem. Key Responsibilities Develop and optimize lithographic patterning of nano- and meso-scale structures, such as gratings, waveguides, cavities, and metamaterials for quantum and THz devices Integrate
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, advanced computational techniques, and data science. The project involves: Materials Development Platform that will enable redox molecule optimization via predictive simulations, database management, and AI
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optimize epitaxial growth of complex oxide nanostructures, especially ferroelectrics, via solid-phase epitaxy (SPE) Perform thin-film and device characterization across structural (XRD, AFM, SEM, XPS, TEM