Job Description

This position focuses on advancing the mathematical and computational foundations of interpretable algorithms for dynamical systems and explainable AI. The successful candidate will develop new methods for modelling, simulating, and understanding complex dynamical processes with a focus on Earth system science, and connections to physics-informed learning, and interpretable machine intelligence.

Qualifications

•             Machine learning

•             Explainable AI

•             ⁠Algorithms for the simulation of classical dynamical systems (including climate-relevant targets such as transport, multiscale flows, and extremes)

•             Signal processing, time evolution, and structure-preserving transformations