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Modeling. Machine Learning Interatomic Potential (MLIP) accelerated simulations. Demonstrated ability of coding in Fortran, Shell, or Python with development experiences. Deep knowledge in excited states and
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to analysis of experimental data. Of particular interest will be new approaches for tackling multimodal data, quantifying uncertainty, providing rigorous theoretical guarantees, and modelling complex physics
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python. Experience with machine-learning, such as training large language models. Required Application Materials: CV Cover Letter (1 page) Publication List Additional information: Application date
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types (inorganic solids, polymers, glasses, etc). Desired skills/knowledge: MongoDB databases. Prior development of Model Context Protocol (MCP) frameworks. For consideration, please apply with