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methods, which could include but are not limited to: Kriging surrogate, Polynomial Chaos Expansion (PCE), and Physics-Informed Neural Networks (PINNs) Contribute to the strategic direction of research
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underestimated cloud cover response to aerosol perturbation, pointing a key direction for improving climate projections. You will work closely with a Scientist at ETH Zurich to apply a new Neural Network-Based
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conclude on December 31st 2029. The goal of this research effort is to apply machine learning (ML) techniques, in particular (equivariant) graph neural networks to accelerate the creation of all physical
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