PhD Studentship in Learning, Prediction and Decision Control in Complex Systems

Guildford, United Kingdom
03 Jan 2019
End of advertisement period
31 May 2019
Contract Type
Fixed Term
Full Time

Department of Computer Science

Location:      Guildford
Fixed Term
Post Type:      Full Time
Advert Placed:      Tuesday 16 October 2018
Closing Date:      Friday 31 May 2019

The project will focus on the development of machine learning techniques, including rule-based machine learning and evolutionary learning, for controlling complex networks. The aim of this PhD is to develop a computational framework for steering complex systems and doing so in a predictable and trusted manner. It involves designing effective external interventions to control the system and/or enhance its resilience. Complexity in such systems arises due to

  • scale (lots of things)
  • diversity (different kind of things), and
  • relationships (inter-related and inter-dependent things interacting with each other and their environment in many different ways, and the relationships change over time).

The research will build on existing work with learning classifier systems for making personalised recommendations to rail passengers for their onward journey options (OJPA funded by Innovate UK) as well as control theory and network analysis which is being applied to policy making (funded by EPSRC; and security - cyber-fraud scenarios, risk assessment and mitigation (part funded by H M Government).

The PhD will be supervised by Dr Sotiris Moschoyiannis:

Current research projects:

Co-supervision by Dr Yunpeng Li whose research projects include:

To apply you should have at least an upper second class honours degree (or overseas equivalent) in Computer Science or Mathematics, or a suitable technical science or engineering subject such as Computer Engineering and Electronic Engineering. Preference will be given to those with appropriate MSc or equivalent research/industrial experience in relevant areas. Experience in a relevant area is not required, but advantageous.

The candidate is expected to have demonstrable programming skills and solid mathematical knowledge. Hands-on skills in one of the programming languages is expected, such as Python, Java, or C/C++. In addition, the applicant must have good communication skills and be fluent in English. We look for a candidate that is self-motivated, engaging, and is a team player.

How to apply

Please click the ‘Apply’ button at:

Please prepare to submit : Your CV; All degree certificates and transcripts; Names of 2 referees and ideally both references (if these are not uploaded, offers cannot be made); Cover letter explaining your interests, computer-science and research experience (including examples of previous project work).