The University of Gothenburg tackles society’s challenges with diverse knowledge. 53 500 students and 6 500 employees make the university a large and inspiring place to work and study. Strong research and attractive study programmes attract scientists and students from around the world. With new knowledge and new perspectives, the University contributes to a better future.

Project Assistant

The University of Gothenburg tackles society’s challenges with diverse knowledge. 53 500 students and 6 500 employees make the university a large and inspiring place to work and study. Strong research and attractive study programs attract scientists and students from around the world. With new knowledge and new perspectives, the University contributes to a better future.

The Department of Marine Sciences at the University is Sweden's most complete environment for marine research and marine education, and is one of only a few such organizations in Europe.

 

Tasks

We are looking for a person to work on a scientific project that aims at investigating the cycle of energy associated with the global ocean circulation in ocean general circulation models (OGCM).

The key idea is to track the centre of mass of the ocean, a quantity which depends directly on the strength of the ocean stratification, and form a budget of the tendency terms controlling its variability at different timescales. The goal is to assess what are the leading processes controlling the ocean stratification and associated global meridional overturning.

The analysis will be done offline, using python analysis tools applied on the model outputs of model simulations based on the ocean model NEMO. The project assistant will be in charge of (1) running the idealized simulations on a supercomputer, (2) developing a python-based toolbox to compute the energy budget from model outputs (using in particular the python package xgcm to handle model outputs on a discretized C-grid), and (3) analysing the balance controlling the position and variability of the centre of mass in the simulations.

The ideal candidate should have both a good knowledge of the implied theoretical concepts and of ocean model analysis (NEMO and python/xgcm programming) in order to achieve the project goals.

Experience with working on a supercomputer and processing of large datasets is required.

The candidate must be able to plan, coordinate and carry out their work independently within predefined deadlines and continuously adapt their plans according to the outcomes of their work.

 

Specific tasks include, but are not limited to:

  • Plan and build idealized configurations to be run with NEMO
  • Generate simulations based on various configurations and post-process the output
  • Analyse simulation data and interpret results in view of large scale ocean dynamics
  • Improve and extend the necessary python tools, and organize them into a package

 

Qualifications

  • A Master’s degree in Marine Science, with specialty in Physical Oceanography, is required.
  • Experience in physical oceanography, with an understanding of the energy budget and processes involved in large scale ocean dynamics. The candidate must show experience of working on supercomputers and data analysis of large datasets.
  • Written and oral communication skills including ability to write scientific articles and give scientific presentations.
  • Detailed knowledge of any aspects of modelling with the ocean model NEMO
  • Good skills in Python coding, with the focus on processing raw data formats to produce scientific quality output and improving any functionalities of the toolbox.
  • Excellent communication skills in speech and writing in English is essential.

 

 

Terms of employment

First day of employment: As soon as possible and by appointment.

The employment is limited to 12 months at 50% of full time (FT) from starting date.

 

 

Last day for application

27 October 2021

 

The application must contain

CV with education, training and work experiences list.

A document that explains why you are interested in this job.

 

Information

For further information, please contact Professor Fabien Roquet, email: fabien.roquet@ gu.se.

 

In connection to this recruitment, we have already decided which recruitment channels we should use. We therefore decline further contact with vendors, recruitment and staffing companies.