PhD Studentships: Theory of Machine-Learning on Networks

University of Bristol - School of Mathematics

The project:

This project aims to develop theoretical underpinnings of statistical analysis and machine-learning with complex (e.g. dynamic, multi-modal and/or large-scale) network data. The theoretical questions considered will often be motivated by (and demonstrated on) cyber-security applications, for example: given a graph and two subsets of nodes labelled as nefarious or benign respectively, label the rest of the nodes of the graph; give mathematical guarantees about the procedure, for example, prove that it is consistent under a standard two-community random graph model. The research should lead to wider applications, for example, forecasting and inference based on communication and social networks. As well as building the theory, the student will develop prototype code for distribution, which will involve learning to use state-of-the-art technologies to handle big data-sets. We will seek to disseminate these techniques through collaborations with government, industry and academia. The student will be joining a growing and dynamic research group in theoretical data science, within the Institute of Statistical Science, School of Mathematics, will attend the Academy for PhD Training in Statistics, and will have access to all School of Mathematics’ lecture courses and training at the Advanced Computing Research Centre.

How to apply:

Please make an online application for this project at http://bristol.ac.uk/maths/study/postgraduate/apply/ selecting Mathematics on the Programme Choice page. When prompted in the Funding and Research Details sections of the form specify that you wish to be considered for  Machine Learning DTA studentship

Additional advice on how to complete your application can be found on our postgraduate advice page. http://bristol.ac.uk/maths/study/postgraduate/

Candidate requirements: 

To be considered for this funded PhD studentship, applicants must hold (or expect to receive) a First Class degree (or equivalent) in Mathematics. Knowledge of probability and statistics, particularly point processes, graphs, and time series, as well as programming experience are desirable.

Funding:  

Includes tuition fees, research travel grant and a full stipend at the EPSRC DTA rate (£14,553 2017/18) for 3.5 years.

Contacts:  Dr Patrick Rubin-Delanchy, http://www.bristol.ac.uk/maths/people/patrick-t-rubin-delanchy/index.html.

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Type / Role:

PhD

Location(s):

South West England