Publisher
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Norwegian Meteorological Institute

PhD in Smart Ocean Observations and Drift Modelling for Marine Applications Norwegian Meteorological Institute in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

Four-year PhD position with 25% duty work related to operational/research activities at MET Norway. Salary as a PhD research fellow (code 1017) with a gross annual salary from NOK 575,000 to NOK 650,000, plus standard public-sector benefits through SPK.

Deadline

Oct 21, 2026

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Country

Norway

University

Norwegian Meteorological Institute

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Keywords

Computer Science
Environmental Science
Electrical Engineering
Mathematics
Earth Science
Physics
ML

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About this position

PhD opportunity in Smart Ocean Observations and Drift Modelling for Marine Applications at the Norwegian Meteorological Institute (MET Norway) in Bergen, Norway. The position is hosted by the Division for Oceanography and Maritime Meteorology and is linked to the EU Horizon project EU-FUSION and the Norwegian Research Council-funded WaveForce project.

The research combines ocean observations, drift modelling, machine learning, smart buoys, and marine applications. The work includes developing small directional buoys with telemetry for coastal environments, extending the OpenDrift framework to integrate observational data into drift simulations, adding acoustic sensors, conducting fieldwork at sea and along the coast, and contributing tools and datasets to the European Digital Twin of the Ocean (EDITO) platform.

This is a four-year PhD position with 25% duty work related to operational and research activities at MET Norway, including metocean studies, data processing workflows, and software tools. The successful candidate will be enrolled at the Geophysical Institute, University of Bergen, and will be situated on the university campus.

Eligibility highlights: MSc or similar in data science, computer science, physics, applied mathematics, oceanography, meteorology, or a related field; admission eligibility for the University of Bergen PhD programme; average grade of C or better; strong English skills; willingness to learn basic Norwegian. Python is required, while machine learning, embedded systems, electrical engineering, signal processing, Fourier analysis, acoustic modelling, fieldwork, and git are advantageous.

Funding: Salary as a PhD research fellow (code 1017), gross annual salary NOK 575,000–650,000, with standard pension/insurance/mortgage benefits through SPK.

Application: Submit the application electronically via Jobbnorge.no. Attach CV, motivation letter, diplomas and transcripts (original and translated), publication list if relevant, and two references. Deadline: 21 October 2026.

Funding details

Four-year PhD position with 25% duty work related to operational/research activities at MET Norway. Salary as a PhD research fellow (code 1017) with a gross annual salary from NOK 575,000 to NOK 650,000, plus standard public-sector benefits through SPK.

What's required

Applicants must have an MSc or similar in data science, computer science, physics, applied mathematics, oceanography, meteorology, or a related field. They must meet admission requirements for the PhD programme at the Faculty of Science and Technology, University of Bergen, including an average grade of C or better. Strong written and spoken English is required, and foreign candidates must be willing to learn basic Norwegian. Python programming experience is required; machine learning, embedded-systems programming, electrical engineering, signal processing, Fourier analysis, acoustic modelling, fieldwork, and git experience are advantageous. The candidate should be independent, collaborative, and prepared for travel and research visits abroad.

How to apply

Apply electronically via Jobbnorge.no. Submit a CV, motivation letter, original and translated diplomas and transcripts, list of publications if relevant, and names of two references. Attach certificates and all pages of diplomas, and include an explanation of the grading system for foreign education if applicable.

More information can be found here

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