PhD Studentship: Querying Big Data(bases)

University of Leeds - School of Computing

Name of School Contact : Dr Isolde Adler
Contact details: Dr Isolde Adler –
Degree Level: Research Postgraduate       
Sponsor Name: School of Computing
Residency requirements [1] : International / Home/EU  
Number Available: 1
Fees (£ pa): £18,500 or £4,250 (UK/EU)
Maintenance (£ pa): £14,296
Top up (£ pa) : n/a
Funding type: School/Faculty 

Globally renowned for our teaching and research, we are one of the leading computing schools in the UK, and we host the Yorkshire Computing Network.

The world-leading work of our two research institutes – the Institute for Artificial Intelligence and Biological Systems and the Institute for Computational and Systems Science - feeds directly into our teaching, which means you’ll learn about the latest developments in your field from world-class academics.

Besides having many links with industry, the School of Computing has a large and strongly visible theory group. Follow the links to find out more about what we offer in the School of Computing.

Project Description 

While Big Data are omnipresent in everyday life, our fundamental understanding of Big Data is still surprisingly small. For example, we would like to be able to query huge databases the same way we can query databases of traditional size. Unfortunately, their sheer size often makes it impossible to even look at the whole data set just once. This rules out numerous traditional "efficient" algorithms, as the amount of resources they use is prohibitive. Hence new ideas are required.

This project combines graph algorithms and logic (model theory). It aims at developing models and *extremely efficient* algorithms for huge relational databases. While we will have to pay a price regarding accuracy, we will still provide (slightly weaker, probabilistic) guarantees. We will then identify structural properties of the databases that allow for such extremely efficient algorithms. We will also search for lower bounds to complement the picture. 

Project start date

January 2017 (negotiable)

Duration of funding

3 Years

Minimum academic requirements (required disciplines and grades, e.g. Any Mechanical Engineering discipline, minimum 2(1) Honours)


You must have achieved a bachelor degree with a 2:1 (hons), or equivalent


A good performance in a Masters level course in a relevant subject. We also recognise relevant industrial and academic experience.

English language

If English is not your first language, then candidates must also meet the University’s English language requirements full details can be found on the following link:

How to apply

Please complete an application form which can be accessed via the following link:

Please remember to include the project title and supervisor(s) in your application

[1] For guidance on Home/EU and International student eligibility for research council funding, please see Appendix

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