Postdoctoral Research Assistant in Uncertainty Quantification for Earth-System Prediction University of Oxford
Weather and climate prediction are undergoing a profound transformation. Alongside traditional physics-based forecast systems, machine-learned (ML) weather prediction models, hybrid ML-physics models, and climate emulators are rapidly becoming an integral part of the prediction landscape. While these approaches can achieve remarkable predictive skill, fundamental questions remain regarding the quantification and representation of uncertainty within and between these models. Addressing these questions is essential if their predictions are to be used for scientific understanding and societal decision-making.
The successful candidate will join Principal Investigator Christensen in addressing the long-standing challenge of delivering reliable probabilistic weather and climate predictions. The project will develop innovative approaches to understand, quantify, and ultimately reduce model uncertainty in next-generation Earth-system prediction systems.
The research adopts a seamless perspective in two key ways:
Utilizing insights gained from short-range weather forecasting to improve the understanding of longer-term climate behaviour, and vice versa.
Exploiting advances in machine learning weather and climate models to improve physics-based models, while using physical understanding to enhance machine learning approaches.
By integrating ideas from numerical weather prediction, climate modelling, and modern machine learning, the project aims to develop physically grounded methods for uncertainty quantification that are applicable across the full spectrum of Earth-system prediction. The post-holder will also have the opportunity to contribute to teaching.
Additional Information:
Job Reference: 188107
Hours: Full Time
Contract Type: Fixed-Term (24 months)
Expected Interview Date: October 2026
Hold, or be close to completing, a PhD/DPhil in physics, climate science, computer science, or a closely related discipline.
Strong computational skills, including experience with UNIX/Linux systems.
Proficiency in programming using Fortran, Python, or other high-level programming languages.
Demonstrated ability to conduct original research of international standing.
Ability to integrate ideas from numerical weather prediction, climate modelling, and modern machine learning.
£39,424 to £47,779 per annum
Friday, 25 September 2026 at 12:00 noon (GMT)