Land Surface Processes Computational Scientist

England (GB) Reading
Apr 20, 2017
May 20, 2017
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We seek a motivated and ambitious computational scientist to join the University of Reading’s Land Surface Processes (LSP) team. The post holder will support the University’s LSP 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, 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, as used in Global Climate models, for example for IPCC studies, using advanced workstations, cloud computing, as well as the world’s most powerful supercomputers. It is expected that the post holder will enable innovative experimental campaigns, state-of-the-art model intercomparison studies, and will benefit from co-authorship of peer-reviewed papers.

You will have:

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

For an informal discussion, please contact either Pier Luigi Vidale, Line Manager on +44 (0) 0118 378 7844 or or Anne Verhoef, Co-advisor on

To apply, please click on the apply button below.

Closing date: 21 May 2017.

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.