项目介绍

2026年9月10日

Postdoctoral Research Fellow position

At the Geophysical Institute and the Bjerknes Center for Climate Research, there is a vacancy for a postdoctoral research fellow position in the physics of weather and climate and their representation through machine learning. The position is for a fixed term of 3 years and is part of the project “Reaching AI Projections Trustworthy for Unseen Rainfall Extremes (RAPTURE)”, funded by a European Research Council (ERC) Starting Grant.

About the project/work tasks:

How can we simulate the properties and dangers of extreme rainfall under conditions we are yet to observe, in a trustworthy way? RAPTURE is a five-year project focused on addressing this question which lies at the heart of understanding high-impact flooding in an ever warmer and wetter world. RAPTURE brings together high-resolution physical simulations, machine-learning climate emulators, and new perspectives on the dynamics of weather and climate to understand i) what current simulations of extreme rainfall can already capture accurately, ii) where they need to improve, iii) and how to improve them. Working as part of RAPTURE will build expertise in dynamical meteorology, machine learning for the earth system, and climate hazards research, with opportunities to engage in research collaborations across Europe.

The successful candidate will be an integral part of RAPTURE, training and refining cutting-edge machine-learning emulators and using novel diagnostic tools to understand these emulators’ performance from a physical weather-focused perspective. They will answer important open questions including which data sources are most valuable for producing reliable climate projections, whether certain weather systems are fundamentally harder to model with machine learning than others, and whether we can develop emulators that can be applied to data-sparse regions of the globe. The successful candidate will have the opportunity to shape how these questions are tackled and will be expected to place their own stamp upon their work.

Qualifications and personal qualities:

• Applicants must hold a PhD or equivalent doctoral degree within atmospheric physics, meteorology, climate science or machine learning. PhD-students may apply if defence of the PhD-thesis is completed by March 2027. It is a condition of employment that the PhD has been awarded
• Strong mathematical and analytical skills are required
• An interest in the meteorology of extreme events and in machine learning for the earth system is required
• Strong and demonstrated programming skills are required
• Prior experience with geospatial data analysis in Python, working on scientific HPC environments, the use of machine learning frameworks (e.g. PyTorch) and version control tools (e.g. GitHub) is an advantage
• Applicants must be able to work independently and in a structured manner, and possess strong collaborative skills
• Applicants must have good written and spoken English skills

Personal and relational qualities will be emphasized. Research experience, ambitions and potential will also count when evaluating the candidates.

Special requirements for the position 
The University of Bergen is subject to the regulations for the export control system. The regulation will be applied in the processing of the applications.

About the position of postdoctoral research fellow:

The postdoctoral position is a fixed term position with the primary objective of qualifying the appointee for work in top academic positions.Candidates who lack teaching experience and/or other qualifying competencies will be given the possibility of an extension of the appointment period up to a maximum of four years in total. The position may be extended by up to one year (maximum 4 years in total) if the appointee is granted externally financed research stays abroad. Individuals may not be hired for more than one fixed-term period as a postdoctoral research fellow at the same institution.

For postdoctoral research fellow positions associated with externally financed projects, the completion of the project proposal for the qualifying work, as well as a progress plan, will be developed in cooperation with the supervisor and head of department.

It is a requirement that the project is completed in the course of the period of employment.

We can offer:

• a supportive and professionally stimulating working environment
• position as postdoctoral fellow (code 1352 in the basic collective agreement) and a gross annual salary of NOK 685 900 upon appointment. Further increases in salary are made according to length of service in the position. A higher salary may be considered for a particularly well-qualified applicant
• enrolment in the Norwegian Public Service Pension Fund
• good welfare benefits

Your application must include:

A cover letter providing:

• a brief account of the applicant’s research interests and motivation for applying for the position
• a detailed justification of your qualifications in relation to the listed requirements, explaining how you meet each criterion. Additionally, you should address the “advantages” mentioned above, as these will be taken into account when ranking the candidates

(Note: Generative AI will not be used in evaluating applications and it is expected that your cover letter is likewise prepared without the use of generative AI)

• the names and contact information for two referees. One of these should be the main advisor from the PhD programme. If this is not the case, a short justification should be given in the application
• CV
• transcripts and diplomas. If you have not yet completed your PhD degree, please submit a statement from your institution confirming the expected date of award of your degree. Your PhD degree must be documented with transcripts and/or diploma, alternatively a confirmation from your institution on completed degree, by March 2027
• relevant certificates/references
• a list of any works of a scientific nature you consider relevant to demonstrating your academic achievement and potential. This includes published papers, or other contributions including but not limited to open-access preprints, contributions to scientific software, organisation of conferences or workshops, or science communication activities