Computing PhD

The University of Brighton has an international reputation for research in computing, notably in areas of security systems, heritage technologies, Vetronics (Vehicle Electronics), user-experience and natural language generation.

Our supervisors across the broad scope of PhD Computing include world-leading experts in their subject areas with extensive track records in PhD supervision. The university provides a comprehensive training scheme to support all postgraduate students. Our aim is to train the next generation of computer scientists to produce world-class research that has strong academic, societal, industrial and economic relevance. The skills our students acquire are designed both to support their doctoral research and enhance their future employability.

With employability one of our key objectives, our computing graduates go on to diverse future careers, from AI start-ups, data science jobs in industry and the public sector, to academic careers at UK and international universities.

Apply to 'Computing Engineering and Mathematics' in the portal

Key information

benefit from a supervisory team comprising two or sometimes three members of academic staff. Depending on your research specialism you may also have an additional supervisor from another school, another research institution, or an external partner from government or industry.
be provided with desk space and access to a desktop PC, either in one of the postgraduate offices on the 6^th floor of the award-winning Cockcroft Building, or within the adjacent Huxley Building.
benefit from access to a range of electronic resources via the University’s Online Library, as well as to the physical book and journal collections housed within the Aldrich Library and other campus libraries.
be able to use various state-of-the-art research facilities on the Moulsecoomb site.

Academic environment

Our research environment boasts the Centre for Secure, Intelligent and Usable Systems and the Applied Data Analytics Research and Enterprise Group which offer world-leading expertise in these areas. PhD students are active full members in these two research groupings, contributing to events and activities.

Moreover, the Division offers a range of subject-specific training opportunities (currently undergoing review and development) to complement the University’s more general research skills training programme for doctoral students.

The School of Architecture, Technology and Engineering hosts weekly Computing Research Seminars with a line-up of external and internal speakers, in which PhD students are encouraged to participate, both by attending and presenting seminars. Coming together for these seminars ensures broad knowledge of state-of-the-art research on a variety of topics, and enables staff and students to network and engage with other researchers in a professional context.

We actively encourage students to contribute to our strong and vibrant research community by publishing their research and attending external conferences around the world, for which funding is available. Our research themes include:

3D and 2D visualisation and digitisation: digital fabrication, virtual and immersive environments, visual analytics
Applied data analytics methods for image, text and structured numerical data, in particular for health, business intelligence and remanufacturing applications
Diagrammatic visualisation, logics and reasoning: visual ontology engineering, software and system modelling, usability of diagrams
Knowledge engineering: knowledge-based AI methods, ontology engineering, repository architectures and semantic metadata
Natural language generation: neural-network methods for text generation, data-to-text, automatic image description, evaluation
Security, privacy, and trust engineering: computer security, intrusion detection, cyber situational awareness, blockchain security and privacy
Text analytics: relation extraction, document classification, sentiment analysis, methods for messy user-generated text
User experience: user modelling, user profiling and recommender systems

Some of our supervisors

Prof Karen Cham

I am interested in Supervising practice based work that contributes to the development of Industry 4.0 transformational, parametric and/or generative systems, particularly with regards human factors, ethics and instance of the singularity. Applications of cognitive systems design, machine learning, computer vision for new technologies such as BCI, 5G MEC, IoT complex deployments, in Volatile, Uncertain, Complex and Ambiguous scenarios particularly welcome.

For example :

digital transformation of values / policy / ideology / law
commercial applications of biometric interfaces
psychometric hypernetworks in MNOs
social and cultural applications of Blockchain & Cryptocurrencies
5G native user experience
human centred Mobile Edge Computing (MEC)
HCD and network slicing applications
cognitive / neural networks
behavioural Internet of Things (IoT)
causal AI
intelligent personas
digial immortality
Internet of Mind (IoM)

Dr Alexey Chernov

I am interested in supervising postgraduate research projects related to mathematically intensive methods of machine learning. My main area is sequential online forecasting, particularly prediction with expert advice. I am also interested in reinforcement learning (especially as a generalisation of online forecasting), kernel methods and topological data analysis.

Dr Roger Evans

I am interested in supervising topics in the theory and application of lexicalist linguistic representations, including inheritance-based, probabilisitic and distributed approaches, and hybrid representations.

Recent PhD student topics include computational lexicography, text analytics, sentiment analysis, semantic metadata, recommender systems and microservice software architectures.

Dr Andrew Fish

I am interested in supervising across a wide range of areas in Mathematics and Computing, on topics with a visual aspect. For example, areas could be in knot theory (Mathematics), or visual representations, languages, models and interfaces, with application domains such as security and privacy (Computing). I have experience of successful co-supervision across a wide range of areas/disciplines and am a UKCGE Recognised Research Supervisor.

Dr Michalis Pavlidis

If you are interested in a PhD under my supervision and you are willing to work hard with me in my research area (cyber security and privacy), please feel free to contact me. Several thesis topics, as well as MSc and undergraduate projects, are available.

Dr Karina Rodriguez Echavarria

My research interest includes the documentation and visualisation of heritage collections, embedding semantics and knowledge to heritage 3D digital assets as well as the use of 3D documentation for producing 3D printable products to support the exhibition and conservation of heritage artefacts. Research topics for supervising includes:

i) 3D digitisation/imaging and 3D digital collections

ii) generating complex, diverse and linked data resources,

iii) semantic technologies, including shape analysis, shape recognition, search and browse,

iv) community involvement with heritage by the use of mobile technologies and social media,

v) design and engineering of objects by digital fabrication technologies.

vi) Sustainability and business aspects for the digitisation of heritage assets, including blockchain technologies and NFT

Dr Anestis Touloumis

I am interested in supervising postgraduate research students in categorical data analysis, multivariate analysis and high-dimensional statistics.

Dr Simon Walters

I’m interested in research supervision in: electrical, electronic, automotive, mechanical and aeronautical engineering, including computer science - intelligent systems applications. I have particular interest in: power and high voltage systems, power electronics, intelligent systems - neural networks and fuzzy logic.

PhD Students:

Name

Thesis

Rama Rahimi (2022-present)

TBA

Bartosz Płoszaj (2020-present)

TBA

Alan Thomas (2014–present)

Intelligent optimisation techniques for minimising transient vehicle emissions

Shaun H Lee (2011)

Intelligent techniques for improved engine fuel economy

Merrenna Manula De Zoysa (2003)

Neural network estimation of air-fuel ratio in internal combustion engines

Nicolas Miché (2002)

Gas Flow Analysis of a Uniflow Diesel Aero-engine

Dr Marcus Winter

I am interested in supervising postgraduate research students in ubiquitous computing, human-computer interaction and applied machine learning in the contexts of education, cultural heritage and public engagement.

For further supervisory staff including cross-disciplinary options, please visit research staff on our research website.

Making an application

You will apply to the University of Brighton through our online application portal. When you do, you will require a research proposal, references, a personal statement and a record of your education.

You will be asked whether you have discussed your research proposal and your suitability for doctoral study with a member of the University of Brighton staff. We recommend that all applications are made with the collaboration of at least one potential supervisor. Approaches to potential supervisors can be made directly through the details available online. If you are unsure, please do contact the Doctoral College for advice.

Please visit our How to apply for a PhD page for detailed information.

Fees and funding

Funding

Undertaking research study will require university fees as well as support for your research activities and plans for subsistance during full or part-time study.

Funding sources include self-funding, funding by an employer or industrial partners; there are competitive funding opportunities available in most disciplines through, for example, our own university studentships or national (UK) research councils. International students may have options from either their home-based research funding organisations or may be eligible for some UK funds.

Learn more about the funding opportunities available to you.

Tuition fees academic year 2021–22

Standard fees are listed below, but may vary depending on subject area. Some subject areas may charge bench fees/consumables; this will be decided as part of any offer made. Fees for UK and international/EU students on full-time and part-time courses are likely to incur a small inflation rise each year of a research programme.

MPhil/PhD
	Full-time	Part-time
UK	£4,500	£2,250
International (including EU)	£15,126	£7,563
International students registered in the School of Humanities and Social Science or in the School of Business and Law	£13,326	£6,663

Professional doctorate
Full-time	Part-time
N/A	£2,673 (UK/EU)

PhD by Publication
Full-time	Part-time
N/A	£2,250 (UK)

Contact Brighton Doctoral College

To contact the Doctoral College at the University of Brighton we request an email in the first instance. Please visit our contact the Brighton Doctoral College page.

For supervisory contact, please see individual profile pages.