Land Surface Processes Computational Scientist

University of Reading - Department of Meteorology

Previous Applicants Need Not Apply.

The post holder will support the University of Reading Land Surface Processes programme in all aspects of the modelling workflow, improving the overall technical and scientific performance of land surface models such as JULES, CLM and C-Tessel, including code portability (on a number of HPCs), scalability, data management and analysis, as well as the associated workflow infrastructure.

Scientists working in this area utilise and develop world leading numerical models of the land surface, using advanced workstations, cloud computing, as well as the world’s most powerful supercomputers.

This activity is part of the University’s Environment Theme and relates to a number of research divisions within this theme, e.g. Climate-, Weather-, Environmental Science and Earth Observation and Space Divisions. Scientific research related to the land surface is conducted throughout a number of cross-cutting research institutes (Walker Institute), centres (Centre for Past Climate Change; Soil Research Centre) and clusters (LandSurfaceProcesses@ReadingWater@Reading).

The University of Reading Land Surface Processes programme also engage internationally in the co-design of modelling systems that span conceptual models, all the way to state-of-the-art numerical models. Further particulars are available on request.

You will have:

  • Excellent computational and programming skills including FORTRAN (90, 95), Python and UNIX/Linux shell scripting.
  • Experience of working with large, complex environmental simulation systems and underlying infrastructure, including code management and documentation for large collaborative groups.
  • Experience of working with Large Data, including data standards (e.g. NetCDF4, HDF5, GRIB2).
  • Knowledge of High Performance Computing (HPC), parallel programming and numerical modelling.
  • Experience of developing and debugging parallel codes, including codes for data analysis.
  • First degree in a numerical or scientific discipline.
  • Strong analytic and communication skills.

Informal contact details
Contact role: Line Manager
Contact name: Pier Luigi Vidale
Contact phone: +44 (0)118 378 7844
Contact email:

Alternative informal contact details
Contact role: Co-advisor
Contact name: Anne Verhoef
Contact email:

This post is Fixed-term.

Interview date to be confirmed.

Start date as soon as possible.

The University is committed to having a diverse and inclusive workforce and we welcome applications for job-share, part-time and flexible working arrangements which will be considered in line with business needs.

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