Back to search results

PhD Opportunity in Learning, prediction and decision control in Complex Systems

University of Surrey

Qualification Type: PhD
Location: Guildford
Funding for: UK Students, EU Students
Funding amount: £16,000
Hours: Full Time
Placed On: 10th October 2018
Closes: 10th December 2018

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 HM  Government).

Duration of studentship: 3 years

Stipend:  £16,000 p.a, subject to nationality and residence status (see below)

Eligibility: Fees are covered for UK/EU students (in value of £4,260).

Dr Sotiris Moschoyiannis

Current research projects:

  • PI on Real-Time Flow, funded by EIT Digital
  • PI on AGELink, funded by EPSRC IAA
  • PI on Onward Journey Planning Assistant (OJPA), funded by Innovate UK
  • CI on SAFRON, funded by Innovate UK
  • PI on KTP with Clearswift, funded by KTN, Innovate UK

Dr Yunpeng Li

 Research projects:

  • HumBug
  • Invertible particle flow for nonlinear filtering
  • Microwave breast cancer detection
  • Radio frequency (RF) tomographic tracking

Entry Requirements:

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.


  • Bachelor degree in Computer Science (UK equivalent 2:1 classification or above)
  • Interest in verification techniques (e.g. formal methods/analysis) and/or in security and privacy
  • Programming experience (any language)
  • Analytical skills: knowledge of foundations of computer science (e.g., discrete mathematics); ability to think independently
  • Strong verbal and written communication skills, both in plain English (see, and scientific language for publication in relevant journals and presentation at conferences.


  • Master’s degree (UK equivalent of Merit classification or above)
  • Experience in Boolean and/or first order logic
  • Experience in formal verification (model checking, theorem proving or SMT solving)
  • Experience of implementation and/or experimentation with verification tools
  • Knowledge of cryptography and/or information security
  • Proficiency in C++ and/or Java
  • Experience with a functional programming language (e.g., Haskell, Ocaml)


Please click the ‘Apply’ button at: 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).

Contact for enquiries: Dr Sotiris Moschoyiannis

Applications accepted all year round .

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):


PhD tools
More PhDs from University of Surrey

Show all PhDs for this organisation …

More PhDs like this
Join in and follow us

Browser Upgrade Recommended has been optimised for the latest browsers.

For the best user experience, we recommend viewing on one of the following:

Google Chrome Firefox Microsoft Edge