Featured themes

Horizon CDT studentships – Featured themes

As part of the recruitment round for the 2020 cohort studentships, some of our collaborating industry partners have already pre-identified featured themes which are open for applications as part of this recruitment round.

Interested applicants with the required qualifications and skills are able to apply specifically to these opportunities as part of this recruitment round and/or apply to the general 2020 recruitment round under the 2020 PhD studentships page.

All available featured themes will be listed here.

Successful applicants to these featured themes will receive the same benefits outlined on the ‘PhD Studentships 2020 cohort’ page.


Featured Theme 1: Experian

A four year fully-funded PhD Studentship in partnership with Experian

As part of the 2020 cohort intake, the Horizon CDT is recruiting for a suitably qualified and experienced PhD student for an exciting opportunity to carry out collaborative research in partnership with Experian with a focus on data science.

Candidates are expected to have a background in Computer Science, Statistics, Physics, Social Science, Mathematics, Applied Mathematics or Economics. Candidates with backgrounds in other STEM subjects will also be considered if they can demonstrate capabilities in data analytics.

Applicants must have an excellent first degree and demonstrate an enthusiasm for multidisciplinary research.  The studentship is only available to UK/Home and also EU students who have been resident in the UK for a minimum of 3 years.

Experian: Potential identified themes/approaches:

  • Co-creating/sharing data to enable better/fairer/faster decisions
  • Open banking – what does this mean for consumers, how will it drive knowledge about the data, and how will it result in better/cheaper experiences in a responsible way?
  • Machine learning/AI to increase the speed and accuracy of data analysis
  • Discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products
  • Applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. Such as:
    • automate scorecards process using machine learning techniques
    • build recommendation systems
    • improve and extend the features used by our existing models
    • develop internal testing procedures
    • build system for automated fraud detection, etc.
  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Data mining using state-of-the-art methods
  • Extending company’s data with third party sources of information when needed
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Doing ad-hoc analysis and presenting results in a clear manner
  • Creating automated anomaly detection systems and constant tracking of its performance.

About Experian

Experian is the world’s leading global information services company.  During life’s big moments – from buying a home or a car, to sending a child to college, to growing a business by connecting with new customers – we empower confidence.  We help individuals to take financial control and access financial services, businesses to make smarter decisions and thrive, lenders to lend more responsibly, and organisations to prevent identity fraud and crime.

The company has 16,500 people operating across 39 countries and everyday we’re investing in new technologies, talented people and innovation to help all our clients maximise every opportunity.  We are listed on the London Stock Exchange (EXPN) and are a constituent of the FTSE 100 Index.

Current Opportunities

How to Apply


The EPSRC Centre for Doctoral Training in Horizon: Creating our Lives in Data is supported by the Engineering and Physical Sciences Research Council (EPSRC) under grant reference EP/S023305/1.