PhD Research Fellow in Climate Data Analysis and Machine Learning Emulation of Hydrological Models
The Geophysical Institute at the University of Bergen is offering a PhD position within the DYNAMIC-AI project, funded by the Bjerknes Centre for Climate Research. This interdisciplinary project aims to integrate physical modeling, dynamical understanding, machine learning, and hydrological modeling to analyze unprecedented and compound extremes, including wildfires, drought, heatwaves, strong wind, extreme precipitation, and flooding. The successful candidate will analyze extreme precipitation events across Europe using CMIP6 CORDEX climate downscaling ensembles and develop a machine learning-based hydrological model to emulate the hydrological response to extreme precipitation, integrating it into the full DYNAMIC-AI framework.
This PhD position is located at the Geophysical Institute, University of Bergen, Norway. The candidate will be part of the highly international Bjerknes Centre for Climate Research (BCCR), which is the largest climate research center in the Nordic countries.
Key qualifications:
- Excellent academic record, suitable for admission to the PhD program at the Faculty of Mathematics and Natural Sciences, University of Bergen.
- Strong analytical skills in climate data analysis.
- Experience with machine learning methodologies.
- Personal and relational qualities will be emphasized.
- Research experience, ambitions, and potential will also count.
Deadline: September 30th, 2026