The School of Computing welcomes applications for our Computer Science research programmes.
Your research should produce an original contribution in your chosen field of study. You work closely with your supervisor, a member of academic staff, who is your principal source of support. If you choose a research area that has interdisciplinary aspects, you may have more than one supervisor. In addition to regular supervision, you will be supported by a supervisory panel of three academic staff who provide further structured input and guidance.
Supporting your research
We offer an extensive support framework to all our research students. We support you in becoming an effective researcher through a series of weekly workshops taken in the first year. These cover research-specific subjects including how to access journals and review research publications, how to write and publish academic articles and how to present your work at seminars and conferences. You may also attend workshops on key transferable skills including communication, time management and teamwork.
You join one or more of our well-integrated, active research groups where you will be able to test and discuss your ideas and place your research in a broader context.
We host a seminar series for visiting speakers as well as holding regular seminars within our research groups where research students are encouraged to participate. We also host an annual postgraduate conference where you have the opportunity to both present your work and to gain experience as a conference organiser.
Many of our research students earn money by teaching on our undergraduate programmes. We provide teaching development courses in your first year to give you the skills to teach effectively.
About the School of Computing
Our world-leading researchers, in key areas such as systems security, programming languages, communications, computational intelligence and memory management, and in interdisciplinary work with biosciences and psychology, earned us an outstanding result in the most recent national research assessment.
In addition, two of our staff have been honoured as Distinguished Scientists by the ACM and we have also held Royal Society Industrial Fellowships.
As an internationally recognised Centre of Excellence for programming education, the School of Computing is a leader in computer science teaching. Two of our staff have received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education. We are also home to two National Teaching Fellows, to authors of widely used textbooks and to award-winning teaching systems such as BlueJ.
We have strong links with industry including Cisco, IBM, Microsoft and Oracle and are among the top ten in the UK for graduate employment prospects.
In the Research Excellence Framework (REF) 2014, research by the School of Computing was ranked 12th in the UK for research intensity.
An impressive 98% of our research was judged to be of international quality, with 81% of this judged world-leading or internationally excellent. The School’s environment was judged to be conducive to supporting the development of research of international excellence.
Students can gain practical work experience as part of their degree through our industrial placements scheme and KITC (see Study support). Both of these opportunities consolidate academic skills with real world experience, giving our graduates a significant advantage in the jobs market.
Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.
We provide an extensive support framework for our research students and encourage involvement in the international research community.
The School of Computing has a large range of equipment providing both UNIX (TM) and PCbased systems and a cluster facility consisting of 30 Linux-based PCs for parallel computation. New resources include a multi-core enterprise server with 128 hardware threads and a virtual machine server that supports computer security experiments.
All students benefit from a well-stocked library, giving access to e-books and online journals as well as books, and a high bandwidth internet gateway. The School and its research groups hold a series of regular seminars presented by staff as well as by visiting speakers and our students are welcome to attend.
Our taught postgraduate students enjoy a high level of access to academic staff and have their own dedicated laboratory and study room. Students whose course includes an industrial placement are supported by a dedicated team which helps them gain a suitable position and provides support throughout the placement.
Our full-time research students are offered funds for academic conference travel, to assist in publishing papers and getting involved in the international community. You have your own desk and PC/laptop in a research office, which is shared by other research students. We also provide substantial support, principally via one-to-one supervision of research students and well-integrated, active research groups, where you have the opportunity to test and discuss your ideas in a friendly environment. You also go on an activity weekend at an outward-bound centre in the Kent countryside, where you will take part in team-building exercises designed to help you learn how to communicate effectively and work together to solve work-based problems.
Dynamic publishing culture
Staff and research students publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Journal of Artificial Evolution and Applications; International Journal of Computer and Telecommunications Networking; Journal of Visual Languages and Computing; Journal in Computer Virology.
Links with industry
Strong links with industry underpin all our work, notably with Cisco, Microsoft, Oracle, IBM, Agilent Technologies, Erlang Solutions, Hewlett Packard Laboratories, Ericsson and Nexor.
The Kent IT Consultancy
The Kent IT Consultancy provides School of Computing students with consultancy experience while studying. KITC provides a project-based consulting service to small businesses in Kent. Its wide variety of services range from e-commerce solutions and network support contracts to substantial software development projects.
Researcher Development Programme
Kent's Graduate School co-ordinates the Researcher Development Programme for research students, which includes workshops focused on research, specialist and transferable skills. The programme is mapped to the national Researcher Development Framework and covers a diverse range of topics, including subject-specific research skills, research management, personal effectiveness, communication skills, networking and teamworking, and career management skills.
A first or 2.1 degree or advanced/specialist taught MSc in computer science or a related discipline (such as mathematics, business studies or electronics, as long as the degree has a strong computing component).
General entry requirements
All applicants are considered on an individual basis and additional qualifications, and professional qualifications and experience will also be taken into account when considering applications.
Please see our International Student website for entry requirements by country and other relevant information for your country.
English language entry requirements
For detailed information see our English language requirements web pages.
Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways.
Research Groups and Highlighed PhDs
If you are keen to pursue a reseach degree, each of the School of Computing's five research groups has suggested projects: do contact the project proposers or the head of research group to tell us that you are interested.
Programming Languages and Systems Group
Our research involves all aspects of programming languages and systems, from fundamental theory to practical implementation. The Group has interests across a wide range of programming paradigms: object-oriented, concurrent, functional and logic. We research the links between logic and programming languages, the verification of the correctness of programs, and develop tools for refactoring, tracing and testing. We are interested in incorporating safe concurrent programming practices into language design.
The Group is also interested in practical implementation of programming languages, from massively concurrent parallel processing to batteryoperated mobile systems. Particular research topics include lightweight multi-threading kernels, highly concurrent operating systems, memory managers and garbage collectors.
Research areas include:
- theoretical and architectural questions concerning designs for both hardware and software
- abstractions and implementations of concurrency in programming languages
- formal specification of systems and their architecture
- design patterns and tools for enabling the safe and scalable exploitation of concurrency
- compilers, memory managers and garbage collectors
- lightweight multi-threading kernels and highly concurrent operating systems
- refactoring of functional and concurrent languages
- applications of formal methods to provably correct, secure systems
- model checking and abstract interpretation, including applications to discovering security vulnerabilities
- program verification and theorem proving
Computational Intelligence Group
This Group brings together interdisciplinary researchers investigating the interface between computer science and the domains of bioscience and cognition. In terms of applying computation to other domains, we have experts in investigating the modelling of gene expression and modeling of human attention, emotions and reasoning. From the perspective of applying biological metaphors to computation, we research new computational methods such as genetic algorithms and swarm intelligence.
The Group also develops novel techniques for data mining, visualisation and simulation. These use the results of interdisciplinary research for finding solutions to computationally expensive problems.
The Group has strong links with other schools at the University of Kent, as well as with universities, hospitals and scientific research institutes throughout the country and internationally.
Areas of research activity within the group include:
- bio-inspired computing including neural networks, evolutionary
- computing and swarm intelligence
- application of computational simulations in biology and medicine
- systems biology including gene expression modelling
- theory and application of diagrammatic visualisation methods
- data mining and knowledge discovery
- construction of computational models of the human cognitive and neural system.
Security Research Group
This Group is a key partner in the University’s Interdisciplinary Cyber Security Research Centre.
Security of computer systems and the information held on them is becoming even more important as a consequence of society’s increased reliance on electronic devices – with most of these holding valuable information or performing critical operations, and connected through networks of some kind.
The Security Research Group covers a wide range of security topics, including identity management and authorisation, privacy, cloud computing, intrusion detection, intrusion tolerance, network overlays, cryptography, formal methods and reverse engineering for vulnerability analysis. It has a strong involvement with postgraduate teaching in the MSc programmes in Computer Security, Information Security and Biometrics, and Networks and Security.
A main subgroup is the Information Systems Security Group led by the authors of PERMIS, a fully functional open source authorisation (or privilege management) infrastructure written in Java.
Research in the Security group contributes to the Research Councils UK Global Uncertainties programme.
Research areas include:
- public key and privilege management infrastructures
- trust management and metrics and reputation systems
- intrusion detection
- tools for vulnerability analysis
- formal methods for cryptography
- policy-based security
- security and risk management
- privacy and security
- autonomic security
- user-friendly security
- continuous auditing
- cloud security
Computing Education Group
We focus on disciplinary-specific pedagogy, especially the teaching and learning of computer science and programming.
Our research interests focus on understanding the aspects of learning that are specific to computing education, and which range from examining general theories of learning, through thematically focused investigations (such as gender), to tool construction. We examine education from multiple aspects, including supporting computing education research infrastructure, working with teachers, or focusing on student learning.
Areas of interest include:
- building an evidence base of research on early programming education
- tool support for learning and teaching of programming, including custom-made development tools, such as educational programming languages, or development environments, which can adapt to changes in programming paradigms and technology and pedagogical advances
- analysis of data generated as a part of the learning process, which could be text-based, naturally occurring in the classroom (eg, assessments), generated as a reflective process on learning (eg, diaries), or generated from interaction with programming environments.
Future Computing Group
We target the next generation computing paradigms and their applications. The Group has been working on grid/cloud computing (internet II), green computing and virtual computing, etc, for many years. A developed grid/cloud computing platform conforms to the internet standard and can universally accelerate office/database/web/media applications by a factor of up to ten. This work won an ACM/IEEE Super Computing Finalist Award.
The Group’s other important work is on environment-friendly green computing through utilising a revolutionary element – memristor. Most recently, the Group has discovered that memristor has a peculiar effect (they named it ‘delayed switching’ in an IEEE paper). It has demonstrated that power-saving memristors can be packed at least twice as densely as semiconductors, achieving a significant breakthrough in computer storage density.
The Computational Economics and Multi-Agency Systems (CEMAS) Lab is part of this group and conducts research in the intersection between computer science and economics (including finance), and the crossroads between multi-agent systems and cloud computing.
Areas of interest include:
- grid/cloud computing
- green computing
- biologically-inspired computing
- computational economics and finance
- multi-agent systems and distributed artificial intelligence
- evolutionary computation and optimisation
- web-based information retrieval
Staff research interests
Kent’s world-class academics provide research students with excellent supervision. The academic staff in this school and their research interests are shown below. You are strongly encouraged to contact the school to discuss your proposed research and potential supervision prior to making an application. Please note, it is possible for students to be supervised by a member of academic staff from any of Kent’s schools, providing their expertise matches your research interests. Use our ‘find a supervisor’ search to search by staff member or keyword.
Full details of staff research interests can be found on the School's website.
David Barnes: Senior Lecturer
Simulation and modelling for biosciences, the teaching of introductory programming, chess cheating and legacy software.Profile
Dr Fred Barnes: Lecturer
Concurrent programming languages, compilers and run-time systems for and based on the communicating processes model of concurrency (CSP and pi-calculus); low-level programming; operating-systems; memory management; run-time system implementation; distributed, parallel and GPU computing; languages, compilers and formal methods.Profile
Dr Eerke Boiten: Senior Lecturer
Cyber security, including the use of formal methods, cryptography, privacy and data ethics. Refinement.Profile
Professor Howard Bowman: Professor of Cognition and Logic
Human attention, emotions, reasoning; connectionist modelling; symbolic modelling; EEG recording and analysis methods; formal methods and concurrency theory.Profile
Professor David Chadwick: Professor of Information Systems Security
Public key infrastructures; privilege management infrastructures; trust management; identity management; privacy management; policy based authorisation; cloud security; autonomic access controls and internet security research.Profile
Dr Olaf Chitil: Lecturer
Semantics and theoretical foundations of programming languages; type theory; program transformation; compiler construction; message-passing- based concurrency; programming tools; how to write programs.Profile
Dr Dominique Chu: Lecturer
Molecular computing (including biochemical computers), stochastic neural networks, complexity and computation, mathematical modelling of stochastic systems.Profile
Dr Rogerio de Lemos: Senior Lecturer
Software engineering for self-adaptive systems: dynamic generation of management processes, abstractions for supporting self-adaptability and self-organisation, resilience evaluation; self-adaptive dependable and secure systems; architecting dependable systems: abstractions for fault tolerance, and verification and validation of dependable software architectures; software development for safety-critical systems; dependability and bio-inspired computing.Profile
Professor Sally Fincher: Professor of Computing Education
The construction and boundaries of CS education; the teacher perspective, especially teacher decision-making; patterns and pattern languages, their use in knowledge-transfer, and their application to CS pedagogy.Profile
Professor Alex Freitas: Professor of Computational Intelligence
Data mining; the biology of ageing; evolutionary algorithms; bioinformatics.Profile
Dr Colin Johnson: Reader
Bioinformatics; computer simulation in biology; bio-inspired computing including genetic algorithms, genetic programming and swarm intelligence methods.Profile
Professor Richard Jones: Professor of Computer Systems
Implementation of programming languages; memory management; garbage collection, distributed garbage collection; object demographics; program analysis for improved memory management; program visualisation.Profile
Dr Stefan Kahrs: Lecturer
Expressiveness of programming languages, type systems, term rewriting, infinitary rewriting.Profile
Michael Kampouridis: Lecturer
Computational finance; application of computational intelligence (CI) techniques to business-related problems, such as economics and finance; use of evolutionary techniques (eg, genetic algorithms, genetic programming); financial forecasting; intelligent decision support systems for business.Profile
Dr Andy King: Reader in Program Analysis
Abstract interpretation, logic programming and security.Profile
Professor Michael Kolling: Professor of Computer Science
Object-oriented systems; programming languages; computer science education; development environments and tools; visualisation; user interfaces.Profile
Dr Caroline Li: Lecturer
Tools for controlling computer/robot using brain signal; body sensor data fusion for healthcare and sports; methods for diagnosing, classifying and monitoring states of brain health/ illness; signal processing and machine learning methods.Profile
Fernando Otero: Lecturer
Development of ant colony optimisation algorithms for data mining; economic applications of data mining; bioinformatics; evolutionary algorithms, mainly genetic programming.Profile
Scott Owens: Lecturer
Semantics of shared memory concurrency; design of programming languages; formal verification for software and interactive theorem proving.Profile
Dr Peter Rodgers: Reader
Information visualisation; graph drawing; Euler diagrams.Profile
Professor Simon Thompson: Professor of Logic and Computation
Functional programming in Haskell, OCaml and Erlang; refactoring functional programs: tool building, theory and practice; dependently-typed functional programming; testing of complex and concurrent systems using properties; property extraction from test suites.Profile
Gerald Tripp: Lecturer
Techniques for the analysis and control of high-speed packet networks, including system monitoring and network intrusion detection; use of special-purpose hardware and firmware designs to perform high-speed string and regular expression matching.Profile
Ian Utting: Senior Lecturer
Tool support for teaching and learning in CS, especially programming, and especially small and mobile devices; large scale data-driven studies of initial programming education, especially using Black Box.Profile
Professor Frank Wang: Professor of Future Computing; Head of School
Future computing; unconventional computing; non-Turing architecture; cloud computing; big data; deep learning; memristor; neural networks; nature-inspired computing; green computing.Profile
Dr Laura Bocchi: Lecturer
Theory and application of session types, concurrency and service-oriented computing.Profile
Professor Ian McLoughlin: Head of School (Medway)
Speech is the primary communications mechanism for humans, and is increasingly the way we interact with computers and mobile devices. In my research I deal with all aspects of speech, language and hearing, and ally this with powerful machine learning techniques that mimic how human brains acquire language and recognise sounds (machine hearing). My research team also works with speech-impaired patients to develop techniques that enable them to regain the power of speech in their daily lives.Profile
Dr Matteo Migliavacca: Lecturer
Stream processing, database systems, parallel data processing, networked systems, cloud computing, distributed systems, big data.Profile
Dr Palaniappan Ramaswamy: Reader, Admissions Officer (Medway)
Analysis of biomedical signals (such as EEG, PCG and ECG) for various applications: brain-computer interface, biometrics, electrophysiological analysis, cardiovascular disease diagnosis and stress management. Also, analysis of speech and image data for various engineering and computer science applications. Tools utilised: advanced signal processing and machine learning (such as neural networks and genetic algorithms).Profile
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