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MSc by Research in Computational Geoscience

Computational skills are now more in demand than ever, e.g. in high-performance computational (HPC) models, big data, and artificial intelligence (AI).

This MSc by Research in Computational Geoscience offers graduate students opportunities to apply these tools, techniques and models in a range of geoscience topics, including seismology and seismic hazards, plate tectonics, renewable energy and environmental research, and planetary science.

Training aspects of the MSc include working with various staff in Computational Geoscience, weekly seminars on Frontier research in the field, and presentation and writing skills.

Applications are welcome at any time - there is no specific deadline. The list of projects inComputational Geoscience is below.

Research Projects

  • Computing evolutionary history from palaeontological data?
    (Dr Martin Smith)
  • The dynamics of granite-greenstone belts.
    (Jeroen van Hunen, Mark Allen, Nick Gardiner)
  • Lithosphere-scale inheritance in the continents.
    (Ken McCaffrey, Jeroen van Hunen)
  • Time-series analysis in Cambrian stratigraphy.
    (Martin Smith, Matthias Sinnesael)
  • Stochastic modelling of Lower Carboniferous fluvial systems: the Fell Sandstone Northumberland.
    (Stuart Jones, Jeroen van Hunen)
  • Testing Convolutional Neural Networks for geophysical imaging.
    (Stefan Nielsen, Stefano Giani)
  • The Rise and Demise of Ancient Cratonic Lithosphere.
    (Jeroen van Hunen, Mark Allen, Graham Pearson)
  • The Dynamic Origin of the Cameroon Volcanic Line.
    (Jeroen van Hunen, Jenny Jenkins, Linda Kirstein)

Entry: via application form here and following successful interview. For subject specific enquiries please contact the project supervisor, and for general postgraduate enquiries contact:

Duration: 12 months [or 24 months part-time]

Entry requirements: 2.1 Bachelor's degree or above (or equivalent) in a relevant subject.

Assessment: research dissertation.