Postdoctoral Fellow in Weather and Climate Physics

1000scholars

Bergen

On-site

NOK 617,000 - 754,000

Full time

14 days+

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Benefits offered by this job

Pension fund enrollment
Welfare benefits

Job summary

University of Bergen (UiB) invites applications for a Postdoctoral Research Fellow position in the physics of weather and climate and their representation through machine learning. The appointment is for 3 years as part of the RAPTURE ERC-funded project.

The role focuses on developing ML emulators and physics-based diagnostics for extreme rainfall scenarios. The successful candidate will work within RAPTURE, train ML emulators, assess emulator performance from a weather-focused perspective, and

Qualifications

  • PhD or equivalent in atmospheric physics, meteorology, climate science or machine learning. PhD students may apply if defence is completed by March 2027.
  • Strong mathematical and analytical skills are required.
  • Interest in meteorology of extreme events and ML for the earth system is required.
  • Strong and demonstrated programming skills.
  • Experience with geospatial data analysis in Python, scientific HPC environments, ML frameworks (e.g. PyTorch) and GitHub is advantageous.
  • Ability to work independently and collaboratively with good English skills.

Skills

Mathematical skills
Analytical skills
Programming skills
Python (geospatial)
PyTorch
GitHub / version control

Education

PhD or equivalent in atmospheric physics / meteorology / climate science or ML

Tools

PyTorch
Python
HPC environments
GitHub

Job description

UiB - Knowledge that shapes society

UiB shall be among Europe's leading universities, internationally recognized for high quality in research and education. As a societal institution, we shall contribute to sustainable and democratic development and be an attractive and inclusive place to study and work.

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.

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 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
  • 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

(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 application and appendices with certified translations into English or a Scandinavian language must be uploaded at JobbNorge.

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