PhD Research Fellow in climate data analysis and machine learning emulation of hydrological models
University of Bergen, Norway
Closing date: 30 September 2026
There is a vacancy for a PhD position at the Geophysical Institute, University of Bergen in climate data analysis and machine learning emulation of hydrology. The position is for a fixed-term period of three years, with the possibility for a fourth year with career-promoting work (e.g. teaching at the Department), under the project DYNAMIC-AI: Dynamics of Unprecedented and Compound Extremes using AI, funded by the Bjerknes Centre for Climate Research.
About the project/work tasks
The PhD fellow will be part of the Bjerknes strategic project DYNAMIC-AI. DYNAMIC-AI will integrate physical modelling, dynamical understanding, machine learning, and hydrological modelling into a unified framework for analysing unprecedented and compound extremes. The project analyses wildfires, drought, heatwaves, strong wind, extreme precipitation and flooding. By unifying scientific approaches and BCCR expertise, we will obtain a new synthetic understanding that is more than the sum of its parts.
The successful candidate will analyse extreme precipitation events across Europe in the new generation of CMIP6 CORDEX climate downscaling ensembles, and develop a machine learning-based hydrological model to emulate the hydrological response to extreme precipitation. This model will be integrated into the full DYNAMIC-AI framework, propagating uncertainty arising from atmospheric dynamics down to hydrological hazards.
DYNAMIC-AI is an interdisciplinary project, and a collaboration between the University of Bergen, NORCE Research and the Nansen Environmental and Remote Sensing Centre (NERSC). The candidate will work in a highly international working environment as part of the Bjerknes Centre for Climate Research (BCCR) co-located with the Geophysical Institute, University of Bergen. BCCR is the largest climate research centre in the Nordic countries and among the leading centres in Europe with around 300 scientists from 40 countries.