PhD in Computer Science UK

The University of Brighton's international reputation in computer science has been demonstrated through impact studies and outputs at each of the Research Excellence Frameworks (REF2014, REF2021). That reputation is especially notable in areas of machine learning, computing for the arts and cultural heritage, security systems, Fintech, robotics AI, human-centred AI, user-experience and natural language generation.

Our researchers take an applied and impact-orientated stance on research output, tackling the overarching societal, environmental and economic challenges through the development of human-centred and intelligent systems for dynamic and complex environments.

We welcome approaches for PhD computer science projects from a number of areas of specialism. For those who join us, we offer excellent support from supervisory staff and the wider department, enabling you to enjoy life as a researcher and the pathway to completing a meaningful project. 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.

Contact an expert in this field

Successful applicants have invariably had support with their application from one of our academics. We suggest you approach a suitable academic staff member with relevant research interests before progressing with your application.

Overview of computer science research degrees

The University of Brighton has fostered research in computer science for several decades, hosting international names across areas such as security systems, computing for the arts and heritage, user-experience and natural language generation.

Our supervisors across the broad scope of PhD Computer Science include world-leading experts in their subject areas with extensive track records in PhD supervision. They welcome approaches for study in their individual areas of research expertise and for interdisciplinary supervision. The University of Brighton had an outstanding performance in the Research Excellence Framework (REF2021), with researchers in computer science contributing their world-leading and internationally excellent research and significant impact for example through our long-standing work in heritage computing and complementing a history of impact studies in REF2014 that included long-standing work across vehicle electronics, natural language and museum partnerships.

We particularly welcome approaches around our specialist research themes, which include:

Computer graphics and visualisation including digitisation, information management, fabrication, virtual and immersive environments, and visual analytics
Computer science in the context of heritage, culture, museums and galleries
3D and 2D visualisation and digitisation: digital fabrication, virtual and immersive environments, visual analytics
Computer science in the context of heritage, culture, museums and galleries
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

Through our research degree in computer science, 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.

Details of PhD programme in Computer Science

Research supervisors for your PhD research degree

As a research student you will benefit from research supervision comprising two or maximum three members of academic staff. Depending on your research specialism one of those supervisors may be from another school, another research institution, or an external partner.

You will identify your potential supervisor from the early stages of application and they will usually then support you throughout your programme of study, helping you carry out your research interests, guiding your learning of rigorous research methods and preparing you for the next stage of your career.

Contact potential supervisors: You should consider the staff listed below and create a short draft research proposal outlining your research project and identifying your suitability for supervision from that person's research specialism.

Research training and support

The independent research programme for research in computing is balanced and enhanced with a range of support from your supervisors and the extended academic community. You and your fellow postgraduate research students will have the opportunity to attend and present at research seminar sessions at the Computing and Mathematical Science Research Excellence Group. The PhD programme will give you the opportunity to build research skills as well as developing transferable skills essential for employment and practice within architecture and its related fields.

As a member of the Brighton Doctoral College, you will benefit from regular opportunities on a training programme designed to support postgraduate researchers at all stages of the PhD and help them achieve their career goals. Attendance at appropriate workshops within this programme is encouraged, as is involvement with the annual PGR Festival. Academic and technical staff also provide more subject-specific training.

Postgraduate degree resources for computer science graduate students

You will benefit from access to international research resources, including a contemporary range of electronic resources via the university’s Online Library, as well as the physical book and journal collections housed within campus libraries. The library services are connected to national and international collections and students also have the option of inter-library loans.

The Computing and Mathematical Science Research Excellence Group

As a computer science PhD student, you will be an integral part of the School of Architecture, Technology and Engineering and take an active role in a range of intellectual and social activities within the school.

The school hosts weekly Computing Research Seminars at the Computing and Mathematical Science Research Excellence Group 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.

The research group brings together academic interests across computer sciences and mathematical sciences aiming to tackle together the overarching societal, environmental and economic challenges. Our interdisciplinary and multidisciplinary research and innovation tackle the development of human-centred and intelligent systems for dynamic and complex environments. The group collaborates with local, national and international communities and industries through research and knowledge exchange impacting the sustainability and well-being of society as well as the competitiveness of businesses that depend on this research.

Timelapse photo of the Moulsecoomb campus at night

Students in computer science are based at the university's recently developed Moulsecoomb campus, located on the main route into the city centre and the seafront.

Supervisors and academic contacts

We strongly recommend that you apply with the support of one of our academics. By establishing your supervisor from the early stages of application, you will be supported through the application process and can make the best start to your programme of study.

You should consider the staff listed below and create a short draft research proposal identifying your suitability for supervision from that person's research specialism and your place in the wider context of the department's research ambitions. Their contact details are available on their full profile.

Our primary staff supervising in the discipline are listed. For further information on university supervisory staff, including cross-disciplinary options, please visit research staff on our research website.

Dr Almas Baimagambetov

I am particularly interested in implementation-driven projects that convert theory into practice that draw knowledge from the following areas: Computer Science (AI, Data Visualisation), Software Engineering, and Game Development. Recently, I've been working on hand tracking, gesture and speech recognition to control software and hardware. My current project is building a brain for robots. I'm leading the development of the Robotics AI lab in Computing and would be interested in any projects that contribute to Robotics and/or AI. See our AI Robotics (AIR) Force team: https://almasb.github.io/RAI/

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 Barbara S. Lancho Barrantes

My area of expertise is Bibliometrics and Scientometrics. I would be interested in supervising PhD/Master/Undergraduate students at any angle of Bibliometrics and Scientometrics and linking them with data analytics and data science. Some examples of specific potential topics (but are not limited to):

Analyse and examine the relation between economic factors and the amount of scientific productivity within countries, academic institutions, geographic regions and subject areas.
Examine the citation flows between countries or organisations that collaborate.
Analysis of Scientific Research Collaborations (institutional, national, international)
Research on Sustainable Development Goals (SDGs)
Cyber Security, theoretical and practical aspects
Bibliometric horizon scanning methodology for identifying emerging topics.
Analyse the relationship between international collaborations and the mobility of researchers.
Conduct gender analyses based on publication data, especially in the context of the SDGs.
Creation and implementation of new scientometric indicators in open research infrastructures.
Examine the open-access citation advantage.
Analysis of predatory publishing as a threat to research integrity.
Understand the research profiles of Higher Education Institutions and their connection with scientific productivity.
Bibliometric mappings of countries, institutions, disciplines, etc.

These topics are general and can be more detailed once the students show an interest in any of them. I will consider any new proposals and discuss any ideas that come up.

In my papers, I analyse the citation increment among collaborating countries. I have also examined how citation patterns of disciplines and bibliographic database coverage may influence the citation flows between subject areas.

The impact of economic factors on countries' research productivity has been the subject of my recent publications. I used data from citation databases, UNESCO, and the OECD for this purpose. I confirmed the relationship between investment in research and scientific results using multiple linear regression.

As well as understanding the scientific contribution to Sustainable Development Goals (SDGs), I focus my research on the mechanisms to interpret this data, since different databases can produce different results.

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 with your CV. Several PhD topics, as well as MSc and undergraduate projects, are available.

Dr Karina Rodriguez Echavarria

My research interest includes the documentation and visualisation of collections, embedding intelligence as well as the (re)use to support innovative approaches, for instance, to support the exhibition and conservation of heritage artefacts and creative applications. Research topics for supervising include:

i) data analytics for complex, diverse and linked data resources,

ii) 3D digitisation/imaging and 3D digital collections,

iii) discoverability technologies, including AI-based analysis, large scale visualisation novel modalities for search and browse,

iv) community involvement with heritage,

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

vi) Sustainability and business aspects, including metaverse, blockchain technologies and NFT

Dr Panagiotis Fotaris

Dr Fotaris's supervisory interests focus on projects exploring the pedagogic potential of games, escape rooms, generative artificial intelligence, virtual/augmented environments, and social media in the context of computing and design education. Additionally, he is interested in projects that combine creative computing with arts, music, and fashion. (e.g., AI-generated visual art and music, projection mapping, data visualisation, wearable technology, immersive media etc.).

Dr Anestis Touloumis

I am interested in supervising postgraduate research students in machine learning methods, categorical data analysis, multivariate analysis and high-dimensional statistics. Projects are likely to involve development of open-source software to support and disseminate the findings of the research.

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 supervise research students exploring human-computer interaction and applied artificial intelligence topics in education, cultural heritage and public engagement.

I am particularly interested in research-through-design [1] projects generating new knowledge through the iterative, user-centred development and evaluation of design prototypes.

For past work and specific research interests please refer to my project pages.

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[1] Stappers, P. J., & Giaccardi, E. (2017). Research through design. In The encyclopedia of human-computer interaction (pp. 1-94). The Interaction Design Foundation.

Making an application

Once you have prepared a first-rate application you can 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 strongly 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 subsistence 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 2024–25

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	£4,786	£2,393
International (including EU)	£15,900	N/A
International students registered in the School of Humanities and Social Science or in the School of Business and Law	£14,500	N/A

PhD by Publication
Full-time	Part-time
N/A	£2,393

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.