Postdoctoral Appointee – Machine Learning for Weather and Climate

 

Argonne National Laboratory, a U.S. Department of Energy National Laboratory located near Chicago, Illinois, has an opening for a highly motivated postdoctoral appointee in the Environmental Science Division.

Machine learning (ML), specifically deep learning (DL), has been demonstrated to successfully predict the weather for 1-14 days with skill on par with numerical weather prediction at a fraction of the computational cost.

A group of scientists at Argonne in collaboration with UCLA have successfully implemented a state-of-the-art ML weather model called Stormer. The candidate selected for this role will collaborate with this group of scientists to extend the predictability of Stormer to the subseasonal-to-seasonal (S2S) timeframe. This position will utilize generative AI to create a calibrated ensemble system for S2S at high resolution (30-km) to deliver probabilistic weather forecasts beyond 14 days to allow for actionable, local-scale impacts on infrastructure and communities.