ORGANISATION NAMECardiff University
ORGANISATION COUNTRYUnited Kingdom
RESEARCH FIELDProfessions and applied sciences
CAREER STAGEFirst Stage Researcher (R1) (Up to the point of PhD)
This PhD is designed to develop novel mathematics which bridges linear algebra, statistics and optimization, and to introduce new modern techniques for anomaly detection.
The escalation of ‘big data’ has given rise to more considered thought on how optimization can inform statistical procedure as the dimensions of the problem grow. A modern trend has been to form statistical problems as (approximate) convex optimization problems, where the technology is such that existing routines can solve such problems in huge dimensions fairly quickly (Boyd & Vandenberghe, 2004).
An interesting question is how close the solution to the approximate convex optimization problem is to the solution of the original statistical problem. This PhD is set in this context outlined, to tackle the problem of anomaly detection.
This project therefore offers you the novel opportunity not only to work on datasets not usually available to academia, but also to do so in a state-of-the art distributed processing environment.
Datasets that you would work on may include HMRC’s turnover and expenditure data from value added tax returns and HMRC payroll data. ONS is exploring the potential to use these in the compilation of headline economic statistics including gross domestic product (GDP). Robust understanding of these new datasets is crucial in ensuring the quality of market-moving statistics.
What is funded
Full UK/EU tuition fees and Doctoral stipend matching UK Research Council National Minimum.
UK Research Council eligibility conditions apply.
Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK. Applicants with a Lower Second Class degree will be considered if they also have a Master’s degree.