Subject: Community detection is an essential tool in the analysis of complex networks, with diverse applications such as identifying genes related to cancer, uncovering terror cells on Twitter, and understanding links between politicians.
For the simplest case of networks, there has been an abundant body of research, and many effective algorithms have been designed. But for more complex networks, the field is much more sparsely populated, due to the lack of consensus surrounding the definition of a community.
The main focus of this PhD will be on unifying the problem of community detection in directed networks. It will build on a recent framework based on higher-order representations of networks, which has had some success. It will also build on existing work by the supervisors to produce methods tailored to the needs of the intelligence community.
The project will blend cutting edge tools for mathematical analysis with algorithm development and extensive investigation of applications.
Full description here:
Eligibility:Applicants should have a first class or good 2.1 honours degree (or equivalent) in a relevant discipline (mathematics, computer science, engineering-related disciplines, etc. with background in applied mathematics and programming). Highly motivated candidates from non-mathematical backgrounds are encouraged to apply.
The studentship covers full tuition fees and a tax-free stipend for 4 years starting on the 1st of October, with an attractive Research Training Support Grant to facilitate travel to appropriate conferences. To be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship.
Deadline for application: 3rd September 2021.
Contact:To apply, please send your CV and a cover letter to Dr Phil Knight (p.a.knight@strath.ac.uk) or Dr Luce le Gorrec (luce.le-gorrec@strath.ac.uk). You can also contact us for more information.
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