Publisher
source

University of Bergen

PhD Research Fellow in Climate Data Analysis and Machine Learning Emulation of Hydrological Models University of Bergen in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

Sep 30, 2026

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Country

Norway

University

University of Bergen

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Keywords

Computer Science
Environmental Science
Geography
Hydrology
Earth Science
Python Programming
Uncertainty Analysis
Statistics
Physics
ML

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About this position

University of Bergen is advertising a PhD Research Fellow position at the Geophysical Institute in climate data analysis and machine learning emulation of hydrological models.

The position is part of the Bjerknes Centre for Climate Research strategic project DYNAMIC-AI: Dynamics of Unprecedented and Compound Extremes using AI, an interdisciplinary collaboration with NORCE Research and the Nansen Environmental and Remote Sensing Centre. The project combines physical modelling, dynamical understanding, machine learning, and hydrological modelling to study unprecedented and compound extremes such as wildfires, drought, heatwaves, strong wind, extreme precipitation, and flooding.

The successful candidate will analyse extreme precipitation events across Europe using the new generation of CMIP6 CORDEX climate downscaling ensembles and develop a machine learning-based hydrological model to emulate hydrological responses to extreme precipitation. The model will be integrated into the broader DYNAMIC-AI framework to propagate uncertainty from atmospheric dynamics to hydrological hazards.

Eligibility and requirements: applicants must hold, or have submitted, a master's degree in computer science, atmospheric sciences, meteorology, hydrology, or a related field; the master's degree must be awarded before employment. Required skills include Python, Unix/Linux, and handling large climate datasets in native formats such as NetCDF. Experience with hydrological modelling, land surface processes, climate data analysis, or training neural networks is required, and experience with PyTorch, extreme events, statistics, and uncertainty quantification is an advantage. Good English skills and the ability to work independently and collaboratively are expected.

Funding: fixed-term PhD fellowship for 3 years, with a possible 4th year for career-promoting work. Salary is NOK 593,700 gross per year, with pension and welfare benefits.

How to apply: submit a one-page research statement, detailed qualification statement, CV, transcripts and diplomas, references, proof of English proficiency if required, publication list, and a copy of the master’s thesis. Applications must be uploaded through Jobbnorge by the deadline.

Deadline: 2026-09-30.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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