Querying Big Data(bases)
- Self-funded PhD students only
- Number of awards: 1
- Deadline: Ongoing
- Supervisors: Contact Dr Isolde Adler to discuss this project further informally.
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.
Applications are invited from candidates with or expecting a minimum of a UK upper second class honours degree (2:1), and/or a Master's degree in a relevant subject. We also recognise relevant industrial and academic experience.
How to apply
Formal applications for research degree study should be made online through the university's website. Please state clearly in the research information section that the PhD you wish to be considered for is the 'Querying Big Data(bases)’ as well as Dr Isolde Adler as your proposed supervisor.
If you require any further information please contact the Graduate School Office
e: firstname.lastname@example.org, t: +44 (0)113 343 8000.