Postgrad LIVE! Study Fairs

Birmingham | Edinburgh | Liverpool | Sheffield | Southampton | Bristol

Wellcome Trust Featured PhD Programmes
Birkbeck, University of London Featured PhD Programmes
University of Hong Kong Featured PhD Programmes
University of Edinburgh Featured PhD Programmes
University of Manchester Featured PhD Programmes

Automated Big data analysis

This project is no longer listed in the FindAPhD
database and may not be available.

Click here to search the FindAPhD database
for PhD studentship opportunities
  • Full or part time
    Dr A Starkey
    Dr M N Campbell-Bannerman
  • Application Deadline
    Applications accepted all year round

Project Description

The amount of data in today’s world is ever increasing, and has even led to new terms describing this as in Big Data. Fully automated data mining technologies that can be used to understand this data currently do not exist apart from very expensive data mining software suites – which in any case require large amounts of human direction and interaction. The training for these suites is also very expensive resulting in the majority of companies being unable to afford either the time or the expense in using these software packages.

Technology developed at the University of Aberdeen over a number of years and resulting in a spinout company could help in solving this problem. This technology is based on the application of artificial intelligence techniques, as well as exploiting the power of statistical methods alongside modern computational power. It is specifically designed to allow fully automated data analysis and can potentially be applied to any type of problem.

This technology has general applicability and can be used on problems as varied as traditional condition monitoring type problems to financial instrument analysis to genomics analysis to the analysis of social media data. This project will look at improving these techniques and comparing them against other currently easily available methods. In particular, the project will examine the process of determining how important features can be determined, and how data can be automatically transformed to give the features of interest.

This work has great commercial value and will likely be of interest to companies in the data analysis field.

The successful candidate should have, or expect to have an Honours Degree at 2.1 or above (or equivalent) in Engineering, Physics or Computational Science with knowledge of computer coding, algorithims and data analysis.

Funding Notes

There is no funding attached to this project, it is for self-funded students only.


Application Process:

Formal applications can be completed online: You should apply for PhD in Engineering, to ensure that your application is passed to the correct College for processing. Please ensure that you quote the project title and supervisor on the application form.

Informal inquiries can be made to Dr A Starkey ([email protected]) with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Graduate School Admissions Unit ([email protected]).

FindAPhD. Copyright 2005-2018
All rights reserved.