Association of Polar Early Career Scientists


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PhD Research Fellow in Global glacier modeling using machine learning
Oslo, Norway
University of Oslo
  • Graduate Position

A PhD Research Fellow position in Global glacier modeling using machine learning is available at the Department of Geosciences at the University of Oslo. 

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

The fellowship period is 3 years with the possibility of a 4th year with compulsory other work (e.g. teaching duties at the Department of Geosciences). This is dependent upon the qualification of the applicant and the current needs of the department.

Earliest starting date is October 1, 2023 and preferably not later than 1 January 2024.

The research fellow will contribute to the development of a modeling framework suitable to reconstruct and project the multi-decadal/century evolution of glaciers (outside the ice sheets) on a global scale. The work will build on the Python Glacier Evolution Model (PyGEM) but enhance its physical basis such as the surface mass balance and/or glacier dynamics scheme while retaining computational efficiency through inclusion of machine learning techniques. The model will then be used to provide reliable policy-relevant multi-decadal/century-scale global glacier projections and scenarios.

The position is part of the recently funded EU ERC Advanced Grant “Past and Future High-resolution Global Glacier Mass Changes (GLACMASS)”. The research fellow will be part of a growing team of researchers, postdocs and PhD students working on reconstructing and projecting global glacier mass changes using machine learning and data assimilation as part of GLACMASS (see also advertised positions as Postdoctor and Researcher in the same project). Funding is available for conference attendances as well as research visits with external collaborators at universities in Europe and the USA. No fieldwork is anticipated for this project, but possibilities to gain field experience may well arise within other projects in the glaciology group.


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