Use of advanced data analysis and machine learning techniques to interpret AGR reactor data

Primary supervisor

Additional supervisors

  • Gavin Brown

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Other projects with the same supervisor


  • Directly Funded Project (European/UK Students Only)
This research project has funding attached. Funding for this project is available to citizens of a number of European countries (including the UK). In most cases this will include all EU nationals. However full funding may not be available to all applicants and you should read the full department and project details for further information.

Project description

The scope of the PhD will be to develop state-of-the-art data analysis and machine learning techniques in order to best interpret the data coming from the models and experiments of the AGR reactors. As they are producing an enormous amount of data, it is necessary to develop clever analyses techniques to extract the relevant information and efficiently compare the different runs containing different input data. Moreover, the number of configurations of damaged core (position, shape and orientation of the cracks) being infinite, it is necessary to develop techniques that would enable to identify patterns of cracks that are of particular interest to support plant life extension. This would be done by finding correlation between inputs of interest (material properties, configuration of cracks, etc...) and outputs of interest (local deformations of the cores, peak forces, etc...). The extrapolation of the results obtained would enable to find extreme scenarios, compare them to damage tolerances and eventually reduce the uncertainty and the degree of the conservatism of current procedures used in safety cases.

Person specification

For information


Applicants will be required to evidence the following skills and qualifications.

  • You must be capable of performing at a very high level.
  • You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.


Applicants will be required to evidence the following skills and qualifications.

  • You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.
  • You will have good time management.


Applicants will be required to address the following.

  • Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
  • How well does your previous study prepare you for undertaking Postgraduate Research?
  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Why do you believe you are suitable for doing Postgraduate Research?
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