Computer Science and Informatics (MSc by Research) -2 year

There are several research topics available for this degree. See below examples of research areas including an outline of the topics, the supervisor, funding information and eligibility criteria:

Healthcare offers unique challenges for the deployment of machine learning models where the demands for interpretability and performance in general is much higher as compared to most other domains. Given that the cost of model misclassification is potentially high, explanations with respect to how a machine made conclusion is derived play a significant role informing clinicians making unbiased decisions. Knowledge-based systems aim to represent knowledge explicitly via tools such as if-then rules, which allow such a system to reason about how it reaches a conclusion and to provide explanation of its reasoning to end users. Fuzzy systems have been considered effective in building such rule-based systems with one of the most important advantages lying in their inherent interpretability as they support the explicit formulation of, and inference with, domain knowledge, gaining insights into the complex problems and facilitating the explanation of their solutions.

The aim of this PhD project is to develop fuzzy rule-based systems with a particular focus on scenarios of healthcare systems. At the initial phase, the project will look into a number of existing approaches proposed to address the interpretability issues of medical systems, as well as the recently established fuzzy rule-based models. A core part of the project will involve the design and implementation of a specific fuzzy rule-based model that will work with carefully selected healthcare aspects. The implemented system will be evaluated with respect to simulated bench mark data sets first, followed by a close examination of how such a system may perform in collaboration with medical doctors when applied to a diagnostic problem of realistic complexity.

Learning Analytics is an increasingly important area of research which has applications both within education and more broadly within organisations and society. In order to develop effective analytical algorithms it is important to better understand the role of data diagnostics within the context of personalised learning. This research study will investigate this topic using a data-driven approach to learning analytics, in particular considering the potential role for automation within learner support through the use of learning analytics and models of learning success.

We provide a supportive and vibrant research environment for postgraduate researchers (PGRs). Researchers at all levels are encouraged to contribute and collaborate. The Graduate School ensures that postgraduate research is of the highest quality and equips you with the resources that you need to become a successful researcher.

We have an exciting and comprehensive Researcher Skills Development Programme available to all postgraduate researchers. This enables you to broaden your knowledge and access tools and skills which can significantly improve employability. The programme is also mapped onto Vitae’s Researcher Development Framework (RDF), allowing you to benefit from Vitae support as well as our own Programme.

We offer skills training through a programme designed to take advantage of technology platforms as well as face-to-face workshops and courses. The University has subscribed to Epigeum, a programme of on-line research training support designed and managed by staff at Imperial College London which will be accessed via Brightspace, the University’s Virtual Learning Environment. We also subscribe to the University of East Anglia webinar series and The Good Doctorate video training series. We are part of the North West and Yorkshire PGR Training Group that allows PGRs to attend relevant training opportunities at other nearby universities.

There is a wide range of topics which can be researched, including the following research areas:

• Artificial intelligence: planning, autonomous systems, knowledge representation and reasoning
• Information systems: Web-based information systems, semantic web, big data
• Human-Computer Interaction: visualisation, computer games

In the past, research has been conducted in collaboration with prestigious national and international partners from academia (e.g. Oxford, UCL, Bristol, Newcastle, Stanford, Bologna, VU Amsterdam, Vienna) and industry (e.g. British Telecom, IBM, Schlumberger).