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, design of experiments, image and data processing. Position Requirements Recent or soon-to-be-completed PhD with strong background in Physics or Materials Science (within the last 5 years) Physics
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, asphaltenes, resins, and kerogen molecules and contribute to engineering design of upscaled processes. The candidate will be a part of the Applied Materials Division (AMD) within AET at Argonne and will
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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thin film deposition is preferred. Advanced image processing and analysis skills. Experience with micromagnetic simulation is preferred. Ability to work independently as well as in collaboration with a
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). This position focuses on The investigation of coupled land-river-ocean processes in coastal flooding applications by developing a coupled E3SM configuration that incorporates a subgrid-scale version of the MPAS
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. The researcher will develop and apply physical, chemical, and electrochemical models for advanced battery technologies and associated manufacturing processes. This work will quantify and explain relationships
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ferroelectric and other functional materials into photonic architectures for electro-optic and quantum transduction applications Perform full device processing using cleanroom techniques, including electron-beam
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nonproliferation. With guidance, the appointee will : Develop advanced multiscale, multiphysics simulation tools relevant to the modeling of processes involving combined nuclear, chemical, and electrochemical
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modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development
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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing