ExaGEO-funded PhD opportunity at EPCC
3 April 2026
The Exascale computing for Earth, Environmental, and Sustainability Solutions consortium (ExaGEO) Centre for Doctoral Training aims to train the next generation of Earth and environmental scientists to harness the power of supercomputers.
Co-led by EPCC, the University of Glasgow, Lancaster University’s Centre of Excellence in Environmental Data Sciences, and partners from industry and government, ExaGEO accepts a cohort of around 12 students a year across a range of projects.
There is an opportunity to fund one additional home fees eligible PhD student at EPCC for a September 2026 start for either of the projects described below.
Mixed-precision multigrid for weather and climate applications (a CASE studentship in collaboration with the Met Office).
Supervised by Prof Michèle Weiland (EPCC, University of Edinburgh), Dr Eike Mueller (University of Bath) and Dr Thomas Melvin (Met Office).
Modern hardware (primarily GPUs) is evolving to make extensive use of floating–point precisions lower than 64-bit. Lower precision can deliver improved performance through better utilisation of vector units coupled with lower demand on memory and network bandwidth. This project will investigate applying low precision computation to weather and climate simulation codes, such as the Met Office’s new forecasting model LFRic. The focus will be on exploring performance gains to the multigrid solver through mixed precision approaches.
Full details of the project: Mixed-precision multigrid for weather and climate applications
Developing large-scale hydrodynamic flood forecasting models for exascale GPU systems.
Supervised by Dr Mark Bull (EPCC, University of Edinburgh), Dr Maggie Creed (University of Glasgow), Prof Simon Mudd (University of Edinburgh).
Flood forecasting at regional and national scale is imperative to predict the scale and distribution of floodwaters during extreme weather events, mitigating the impact on communities most at risk from flooding. The increasing availability of high resolution topographic and meteorological data provides an opportunity to extend the capability of the LISFLOOD modelling framework to produce large-scale or high resolution flood forecasts at operational timescales. GPU-based exascale HPC systems provide the technological basis to develop forecast models delivering at operational timescales.
Full details of the project: Developing large-scale hydrodynamic flood forecasting models for exascale GPU systems
Applications open
The application deadline is 24 April 2026.
For more information and to apply, see the ExaGeo website.
