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: The design and analysis of computational methods that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance
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physics, materials science, applied mathematics, computer science, or a related field, and no more than five years of experience beyond PhD. Preferred Qualifications: Background in quantum magnetism
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learning, mathematical analysis, mathematics of data, modeling & simulation, multiscale methods, numerical analysis, optimization, ordinary and partial differential equations, numerical solvers, quantum
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