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and application of methods for simulating magnetism, particularly atomistic and multiscale simulations. The successful candidate will have the opportunity to collaborate with leading experimental and
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to investigate and develop novel ceramic electrolytes for next-generation composite solid-state batteries. Particularly halides and sulfides are of interest. By integrating atomistic simulations with experimental
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to develop novel AI and machine-learning methods for accelerated materials discovery. The focus is on combining generative AI, active learning, first-principles simulations, and machine-learning potentials
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