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Additional Information Eligibility criteria Training and experience: A PhD in Materials Science, Computational Chemistry, Physics, or a related field, with a strong background in DFT modeling and experience in
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surface-chemistry trends across selected metals and their oxides. These data will support the construction of a machine-learning force field tailored to NHC–surface systems, enabling large-scale molecular
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collaboration between the Exa-SofT and the Exa-DI projects and better support multi-linear algebra and tensor contractions in exascale CSE applications and Machine Learning. As part of the collaborative process
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