Summary
The Nansen Center is offering a PhD fellow position focused on the development of forecasting techniques using Machine Learning (ML) emulators for Arctic Ocean research. This position is a unique opportunity to engage in cutting-edge climate research as part of an international team.
PhD Fellow in Machine Learning, Nansen Environmental and Remote Sensing Center Bergen, Norway
Designation
PhD Fellow in Machine Learning
| Detail | Information |
|---|---|
| Employer | Nansen Environmental and Remote Sensing Center |
| Location | Bergen, Norway |
| Duration | 3 Years (Full-time) |
| Application Deadline | 30th April 2026 |
Research Area
Machine Learning applications in ocean forecasting, particularly within the context of the Arctic Ocean’s physical and biogeochemical modeling.
Eligibility/Qualification
- Master’s degree (or equivalent) in data science, applied mathematics, machine learning, informatics, or a related field.
- Candidates must be eligible for registration as a PhD candidate at the University of Bergen (UIB).
- Knowledge of physical oceanography is a plus.
- Fluent in both spoken and written English.
Job Description
The PhD fellow will:
- Design the architecture and train a generative emulator from an ice-ocean-biogeochemical model of the Arctic Ocean.
- Assess the reliability of ML forecasts and their inclusion in ensemble data assimilation.
- Utilize forecasting systems like TOPAZ and neXtSIM, alongside Ensemble Kalman Filter and remote sensing data.
How to Apply
Interested candidates should apply via the Nansen Center’s job application page. Include the following documents:
- Curriculum Vitae (CV) with contact information
- Two contact references
Press the “Apply for this job” button on the webpage to submit your application electronically. Note that candidates may be assessed and contacted before the application deadline.
Last Date for Application
30th April 2026
For more information, please contact Research Leader Laurent Bertino at laurent.bertino@nersc.no.
