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Queen's University Belfast

Computer Science - Research

Programme Overview
The School of Electronics, Electrical Engineering and Computer Science (EEECS) aims to enhance the way we use technology in communication, health services, data security and many other related areas.

Pioneering research is the lifeblood of the School and is evidenced by REF 2014, in which 100 per cent of the School's research was judged to be internationally excellent or world leading. Our commitment to research has led to the establishment of ECIT (the £40m Institute of Electronics, Communications and Information Technology) and more recently the Centre for Secure Information Technologies (CSIT), which is the UK's lead university centre for cyber security research.

With the research from these centres, and the spin out companies supported by the School, EEECS is in an excellent position to drive and influence the economy at a local, national and international level.

Entry requirements

Research Degrees (PhD/MPhil/MD/Professional Doctorates)

The normal minimum requirement for admission to a research degree programme is an Upper Second Class Honours Degree from a UK or ROI Higher Education Provider or an equivalent qualification acceptable to the University.

Specific entrance requirements for individual programmes are available via the online Course Finder and we recommend that you also visit School webpages and contact potential supervisors to discuss your proposed research.

Factors taken into consideration by School selectors will include an assessment of an applicant's academic background and research proposal (if applicable). Relevant publications, professional research experience or other achievements by the applicant may also be considered.

Further information is available on Higher Doctorates and PhD by Published Works.

English Language Requirements

If your first language is not English, evidence of an acceptable level of proficiency will be required. In addition, applicants who are non-EEA nationals must satisfy the UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes. Further information is available on the UK Government website.

The evidence should be in the form of a Secure English Language Test (SELT), or another English language qualification acceptable to the University which examines all four elements of language learning Listening, Reading, Writing and Speaking. IELTS Academic and TOEFL internet based tests should be taken within the last two years. Further information is available here.

Details of the English language requirements for entry to each postgraduate taught and research programme can be found in the individual Course Finder pages.

If you have not yet obtained an acceptable English Language qualification at the required level before sending us your application, your formal offer for postgraduate admission will include an English language condition which you must satisfy before the start of your programme.

INTO Queen's University Belfast offers a wide range of English language courses designed specifically for international students.

International applicants

For more information please visit the international section of our website.

Applicants who require assistance with the application process should email the International Admissions team at intl.student@qub.ac.uk

Duration

Mode of study/Duration

Registration is on a full-time or part-time basis, under the direction of a supervisory team appointed by the University. You will be expected to submit your thesis at the end of three years of full-time registration for PhD, or two years for MPhil/MD (or part-time equivalent).

Further enquiries

People teaching you
Ms Elaine Cranston
Electronics,Elec&Comp Science
Email: e.cranston@qub.ac.uk

Application date

Postgraduate Research

There is no standard closing date. You should however check both the University's website and refer to the relevant School/Institute webpage for information on deadline dates for postgraduate funding applications, as these will also determine when your application for admission should be submitted.

Research areas

Research information

Associated Research
Research within the School is organised into research clusters, three of which are:

HPDC (High Performance and Distributed Computing)

KDE (Knowledge and Data Engineering)

SIVS (Speech, Image and Vision Systems)

The research clusters combine strengths by working together on major projects, in many cases in collaboration with key technology companies.

HPDC has been successful in attracting substantial DTI funding for projects (around £3-4m), which have produced exemplary demonstrations of Grid technology in real applications.

KDE researches theoretical and application-oriented issues in soft computing, addressing the latest development and applications of knowledge and data systems for solving extensive, complex, technological socio-economic problems.

Different techniques in the design of advanced knowledge systems are developed and research directions are investigated.

SIVS carries out research in intelligent video surveillance, 3D medical imaging and speech processing. This cluster has also attracted several million pounds in funding for both fundamental and applied speech, image and video applications within the framework of the ECIT institute, a major new cross-disciplinary development in conjunction with Electronic Engineering.

ECIT brings together internationally recognised research groups specialising in key areas of advanced digital and communications technology.

CSIT brings together research specialists in complementary fields such as data security, network security systems, wireless-enabled security systems, and intelligent surveillance systems, and serves as the national point of reference for knowledge transfer in these areas. As well as collaborating to widen perspectives in the other clusters, KDE has used external funding to produce substantial research outputs and technology transfer in the areas of adaptability, optimisation, reasoning under uncertainty, data mining, and knowledge integration