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or model parallel training. Experience with multi-physics simulations on HPC and with ML models. Experience working in a multi-disciplinary research environment. Demonstrated written and oral
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architectural design decisions for massively parallel heterogeneous systems, including pathways that integrate quantum or analog co-processors. Performance Engineering at Scale: Profile, model, and optimize
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, including parallel computing frameworks, C/C++, Julia and/or python Experience with training AI surrogate and/or inverse models Experience working in underground laboratories and/or clean rooms Excellent
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