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.

  • Able to travel in UK and abroad on BBC business
  • An informed knowledge of and passion for the technologies involved in a media organisation
  • Capable of highly original work together with an enquiring mind with well-developed analytical and investigative skills
  • Ability to rapidly acquire new skills and to work with new technologies with little documentation or support
  • This project requires mathematical engagement and ability substantially greater than for a typical Computer Science PhD. Give evidence for appropriate competence, as relevant to the project description.
  • A track record in software and/or electronic engineering, Human-Computer Interaction and/or behavioural scientific research
  • Awareness of emerging trends and developments in relevant technology, gained through project work as part of a relevant degree, extra-curricular project work or employment experience
  • Good written and oral communication skills, able to promote ideas by logical argument and capable of presenting the results of a project in a clear and effective manner
  • Self-motivated, with the drive and initiative to carry out projects according to plan, and the ability to quickly adapt in a fast-changing environment
  • 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.

  • Understanding of the needs of different kinds of BBC users and how to apply this to the development of user interfaces and new kinds of user experience
  • Ability to work as part of a multi-disciplinary team
  • Ability to propose novel ideas involving the application of technology to media content production, and the ability to pitch these ideas convincingly to non-technical people
  • Sound resource management skills and be able to lead, motivate and direct support staff and contractors contributing to the project
  • 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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