The Geophysical Institute at the University of Bergen is seeking candidates for a PhD position in high-resolution numerical modelling and model analysis of the atmospheric water cycle in the Arctic. The position is for a fixed-term period of 3 years with the possibility of a 4th year with compulsory other work, such as teaching duties at the Geophysical Institute. The position is associated with the ERC Consolidator Grant project ISLAS (Isotopic Links to Atmospheric Water’s Sources), funded by the EU-H2020 programme.
The central aim of the ISLAS project is to understand the connection of processes in the atmospheric water cycle, from source to sink. The ISLAS team has recently collected a series of unique airborne and ground-based measurements in the European Arctic during marine cold-air outbreak conditions. We now intensify our efforts to quantify the contribution and efficiency of different processes in the atmospheric water cycle in numerical models. A key tool in this endeavour are constraints from the stable isotope composition of water vapour and precipitation. By combining new measurements with advanced and novel model diagnostics, we want to reveal compensating errors between different physical processes in models, which in turn can provide the basis for more consistent atmospheric water cycle in models. We are now looking for an engaged and highly qualified PhD candidate to join our dynamic, collaborative project team. As a PhD in the Meteorology group at the Geophysical Institute at University of Bergen, you will also be affiliated with the Bjerknes Centre for Climate Research (BCCR). BCCR is the largest climate research centre in the Nordic countries and among the leading centres in Europe. The working environment is highly international with around 200 scientists from 37 countries.
Work tasks
The successful PhD candidate will develop and apply advanced numerical model diagnostics. A particular objective is to work with time-step wise output within subdomains in high-resolution models to enable the most direct comparison of observations with model simulations. Additional diagnostics include Lagrangian particle dispersion modelling, Eulerian water vapour tracers, and isotope-enabled models. From a combination of observational case studies and sensitivity analysis using ISLAS campaign data, the contributions and efficiency of different processes (e.g., evaporation, mixing, and cloud microphysics) will be evaluated. To this end, the candidate will work with a wide range of observations, including airborne and ground-based measurements with in-situ and remote-sensing instrumentation in an Arctic environment. Working within this ambitious PhD project provides room for the creative exploration of a wide set of numerical tools and measurement data. Therefore, the work requires frequent engagement and exchange with other project participants and collaborators.
Qualifications and personal qualities
- Applicants must hold a MSc or an equivalent degree within meteorology, climate dynamics, environmental science, or other relevant disciplines. Master students can apply, provided that they have submitted their master’s thesis for assessment prior to the application deadline. It is a condition of employment that the master’s degree has been awarded.
- Enthusiasm to understand the inner workings of models for numerical weather and climate prediction is required
- Expertise in scientific scripting and programming and data analysis (e.g., Python, Matlab, R, C++, FORTRAN) is required
- Proficiency in both written and oral English is required
- Ability to work independently and in a structured manner is required
- Ability to work under supervision and collaboratively is required
- Ability to actively communicate and co-operate within a larger research team is required
- Experience with LINUX environments and handling large datasets is an advantage
- Experience with Eulerian and Lagrangian numerical model diagnostics is an advantage
- Experience from meteorological field campaigns in Arctic environments is an advantage
- Experience in teaching and outreach activities is an advantage
Personal and relational qualities will be emphasized. Ambitions and potential will also count when evaluating the candidates.
About the PhD position
The fellowship will be for a period of 3 years, with the possibility for a 4th year, consisting of 25 % compulsory work (e.g. teaching responsibilities at the department) distributed over the employment period. The 4th year is contingent on the qualifications of the candidate and the teaching needs of the department and will be decided by the head of department upon appointment. The employment period may be reduced if you have previously been employed in a qualifying post (e.g. research fellow, research assistant).
About the research training
As a PhD Research Fellow, you must participate in an approved educational programme for a PhD degree within a period of 3 years. The deadline for applying for admission to the PhD programme at The Faculty of Mathematics and Natural Sciences is 2 months after you start your position or after the start of the research project that will lead to the PhD degree. It is a condition that you satisfy the enrolment requirements for the PhD programme at the University of Bergen.
We can offer
- a good and professionally stimulating working environment
- salary at pay grade 54 (Code 1017/Pay range 20, alternative 10) in the state salary scale. This constitutes a gross annual salary of NOK 501 200,- . Further promotions are made according to length of service in the position.
- 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 one-page research summary, describing your master thesis work and your experience with numerical models.
- CV
- the names and contact information for two referees. One of these should be the main advisor for the master’s thesis or equivalent thesis
- transcripts and diplomas showing completion of the bachelor’s and master’s degrees. If you have not yet completed your master’s degree, please submit a statement from your institution confirming that the master’s thesis has been submitted.
- relevant certificates/references
- approved documentation of proficiency in English (if required, cf. English language requirements for PhD admission)
- list of scientific publication and other relevant outreach and communication activity
The application and appendices with certified translations into English or a Scandinavian language must be uploaded at Jobbnorge.
General information
For further details about the position, please contact Prof. Harald Sodemann by email (harald.sodemann@uib.no) or phone (+47 55 58 29 74).
The state labour force shall reflect the diversity of Norwegian society to the greatest extent possible. Age and gender balance among employees is therefore a goal. It is also a goal to recruit people with immigrant backgrounds. People with immigrant backgrounds and people with disabilities are encouraged to apply for the position.
The University of Bergen applies the principle of public access to information when recruiting staff for academic positions.
Information about applicants may be made public even if the applicant has asked not to be named on the list of persons who have applied. The applicant must be notified if the request to be omitted is not met.
The successful applicant must comply with the guidelines that apply to the position at all times.
For further information about the recruitment process, click here.
Life as a PhD candidate at UiB
Marion Claireaux tells about life and work as a PhD candidate at UiB.
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About UiB
The University of Bergen is a renowned educational and research institution, organised into seven faculties and approximately 54 institutes and academic centres. Campus is located in the centre of Bergen with university areas at Nygårdshøyden, Haukeland, Marineholmen, Møllendalsveien and Årstad.
There are seven departments and several centres at Faculty of Mathematics and Natural Sciences. Read more about the faculty and departments.