Postdoc: Physics-Informed ML for Excited-State Chemistry
Lawrence Berkeley National Laboratory
Lawrence Berkeley National Laboratory is seeking a Postdoctoral Researcher in Scientific Machine Learning & Computational Chemistry to advance physics-informed, symmetry-aware ML models for nonadiabatic excited-state simulations. You will build equivariant graph neural networks and connect them to nonadiabatic dynamics workflows. The role emphasizes developing robust research software, validating models on energy-relevant systems, and contributing to open-source tools while collaborating with #J-18808-Ljbffr Lawrence Berkeley National Laboratory
Vacancy posted 1 day ago
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