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Position Requirements Ph.D. in Materials Science, Physics, Electrical Engineering, Applied Physics, or a related field (completed or soon-to-be-completed) Demonstrated expertise in nano- and mesoscale
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, physics, computer science, and/or data science Demonstrated accomplishments in materials informatics, scientific machine learning, or AI-guided experimental design Strong Python and scientific computing
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. Position Requirements A formal education in Physics, Materials Science, Chemistry, or a related field at the PhD level with zero to five years of employment experience. Demonstrated experience with high
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-completed PhD with strong background in Materials Science or Physics (within the last 5 years) Considerable experience in understanding magnetic-domain physics in thin film and/or nanostructured materials
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interdisciplinary teams within the Materials Science division at the Argonne National Laboratory and external collaborators. Position Requirements • Ph.D. (completed or soon to be completed) in Physics, Materials
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beyond traditional error estimators, creating physics-based adaptation algorithms that intelligently predict where refinement will be most beneficial for smarter, more efficient simulations. We seek