Computer Science: Funded PhD Studentships: 6 Projects Available
Closing date: 30 April 2017
Swansea University is a UK top 30 institution for research excellence (Research Excellence Framework 2014), and has been named Welsh University of the Year 2017 by The Times and Sunday Times Good University Guide.
Swansea Science DTC is a community committed to undertaking world-class research that has a positive impact globally and we have a number of fully-funded PhD scholarships for 2017/2018 entry.
Supervisor: Daniel Archambault
Project Title: DTC CS 10 - Social Network Analysis for Mental Health Support
Description: Many health issues, in particular mental health issues, have a social component that influences vulnerable members of a population in contact with symptomatic cases; within psychiatric epidemiology this is known as social contagion (e.g. social ties influence self harming behaviours on platforms such as Instagram). In this project, the successful candidate will explore the area between graph mining (a technique used in big data analysis) and visualisation to develop methods to aid the analysis and understanding of social contagion within social media networks. The candidate is expected to have a background in visualisation and would benefit from an emerging collaboration between Swansea University and the University of Glasgow on this topic.
Supervisor: Ulrich Berger
Project Title: DTC CS 11 - Computing with Infinite Data
Description: Infinite or virtually infinite data occur naturally when processing very large data sets or exact real numbers, and computing with such data poses many theoretical and practical challenges. Computing with Infinite Data is a four year Horizon 2020 project, starting in April 2017, that will provide the opportunity and means for two PhD students to spend several months abroad in order to facilitate research and knowledge exchange in that area. The proposed research will focus on logical methods for the specification and extraction of formally verified algorithms for infinite data.
Supervisor: Oliver Kullmann
Project Title: DTC CS 12 - Understanding Inconsistency
Description: Via SAT solving, that is deciding propositional satisfiability, very hard problems can be solved, but if the problem turns out to be unsolvable (inconsistent), then we typically don’t know where this inconsistency comes from, how to locate it. This project is about the theoretical, and possibly also practical foundations of understanding such unsolvability for propositional logic. A certain background in discrete mathematics and logic, and a certain capability for pioneering research would be good to find in the applicant.
Supervisor: Robert S Laramee
Project Title: DTC CS 13 - Interactive Visualization of Big, High-Dimensional Data
Description: The ubiquitous collection and archiving of big, complex data sets is certainly one of the top challenges of the 21st century. This project develops novel, advanced data visualization and visual analytics algorithms and techniques the address this challenge.
Supervisor: Adeline Paiement
Project Title: DTC CS 14 - Machine learning methods for health and social care
Description: In this project, the successful candidate will learn and develop state-of-the-art machine learning methods, such as deep learning techniques, to assist in health and social care delivery. Machine learning methods will be designed to recognise and understand subjects’ activities and behaviours, and link them to their physical and mental health status. The project will be within a team of researchers experienced in machine learning and deep learning, and in close collaboration with experimental psychology departments at Swansea and Bristol Universities.
Supervisor: Monika Seisenberger/Phil James
Project Title: DTC CS 15 - Modelling Train Control Systems
Description: The European Rail Traffic Management System (ERTMS) is a state-of-the-art train control system, currently in test use on a few lines in UK only, which aims at improving the performance and capacity of the rail traffic systems, without compromising on their safety. The aim of this project would be to make a contribution to the modelling and verification of such a train control system and to consider as well capacity measurements. The modelling will be done in Real-Time-Maude, a system developed for the specification and verification of Hybrid Systems.
Candidates must have a First, Upper Second Class Honours (or equivalent) or a Master’s degree in a relevant discipline.
Informal enquiries before the deadline are welcome by emailing the project supervisor.
These are three year fully-funded scholarships, open to UK/EU candidates which include an annual stipend of £14,553 plus full UK/EU tuition fees.
Applications from overseas candidates are welcome, but candidates would be required to pay the difference between the UK/EU tuition fees and the overseas tuition fees.
How to Apply
Candidates should only apply for one project.
Candidates must complete and submit the following documentation by the stated deadline.
To apply for this scholarship, please download the research scholarship application form and return it to the College of Science with the following:
- Academic References – all scholarship applications require two supporting references to be submitted. Please ensure that your chosen referees are aware of the funding deadline, as their references form a vital part of the evaluation process. Please either include these with your scholarship application or ask your referees to send them directly to firstname.lastname@example.org
- Academic Transcripts and Degree Certificates – academic transcripts and degree certificates must be submitted along with the scholarship application by the funding deadline. We will be using these to verify your academic qualifications.
- CV – please include a recent CV
- Candidates should use the ‘Supplementary Personal Statement’ section of the application form to explain why the award they are applying for particularly matches their skills and experience and how they would choose to develop the project. Candidates are also required to identify the supervisor associated with their project explicitly in their application.
All successful candidates are required to participate in the Swansea Science DTC training activities throughout their degree.
Please email the documents to email@example.com or post them to
Recruitment and Marketing Team
College of Science
Swansea SA2 8PP
For more information please click "Further Official Information" below.
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