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Intelligent Big Data Management

School of Electronics, Electrical Engineering and Computer Science | PHD
Funding
Funded
Reference Number
EEECS/2025/ZL2
Application Deadline
28 February 2025
Start Date
1 October 2025

Overview

The emerging age of big data is leading us to an innovative way of understanding our world and making decisions. As the name suggests, this “big data” age comes with a stunning and continuous data growth. For example, it has been estimated that 2.5 quintillion bytes of data are produced by humans every day (there are 18 zeros in a quintillion), and 463 exabytes of data will be generated each day by humans as of 2025. Such a data growth brings tremendous challenges to data management that plays a prerequisite role in business intelligence and big data analytics (BDA).

It is worth noting that when implementing BDA, there are inevitably more challenges than traditional data analytical scenarios. On one hand, big data itself can cause significant performance problems in application programs in general, especially when involving databases. On the other hand, following the No-Free-Lunch theorem, various data types and analytical demands might require completely different BDA applications involving different time and space complexities. For example, de facto BDA workload characteristics extremely vary, and the typical ones include batch processing for offline analytical jobs, stream processing for real-time processing of data, query-processing with transactional features, and even a combination of them.

Driven by the needs and challenges of BDA (that essentially reveals the potential values of datasets and completes the value chain of big data), it is crucial and valuable to investigate effective and efficient techniques, strategies, patterns, and theories of big data management.

Big data management is the organisation, administration, and governance of large volumes of both structured and unstructured data. This project will mainly focus on “data gravity”, “data friction”, and “data transformation” to investigate big data management.

• Data gravity refers to the tendency of data to accumulate and attract further data and applications, which may trigger difficulty and extra cost when moving data away from its storage.
• Data friction is a resistance that impedes the transfer of data between systems, which may result in processing delays, increased costs, and higher energy consumption.
• Data transformation is the process of converting, cleansing, and structuring/restructuring data into a usable format that can be analysed to support decision making processes, and to meet the needs of a target system.

Despite their disadvantages, different levels of data gravity and data friction would be needed when dealing with different types and/or techniques of BDA jobs. For example, the privacy-critical BDA scenarios will require a high level of data friction, while the quantum computing-based BDA solutions will favour heavy data gravity.

Data transformation, on the other hand, can potentially relieve the negative effects of data gravity and data friction. For example, the coding theoretic techniques can significantly speed up distributed machine learning. This project will particularly focus on Compact Data Structure (CDS) for data transformation, for taking advantage of CDS techniques that can represent data in little space as possible, plus a sublinear amount of extra space to provide fast operations without any decompression activity.

Note that the specific research topic of this project will be further discussed and determined based on the student’s interests and knowledge base. For example, you may want to develop a generic big data management framework that considers all kinds of BDA logic; or you may focus on a specific BDA scenario to manage and/or optimise data gravity and friction, e.g., for a hybrid BDA job that involves both Edge computing and Quantum computing. So, please feel free to open your mind and have your specific proposal(s) along this research direction.

Funding Information

To be eligible for consideration for a Home DfE or EPSRC Studentship (covering tuition fees and maintenance stipend of approx. £19,237 per annum), a candidate must satisfy all the eligibility criteria based on nationality, residency and academic qualifications.

To be classed as a Home student, candidates must meet the following criteria and the associated residency requirements:
• Be a UK National,
or • Have settled status,
or • Have pre-settled status,
or • Have indefinite leave to remain or enter the UK.

Candidates from ROI may also qualify for Home student funding.

Previous PhD study MAY make you ineligible to be considered for funding.

Please note that other terms and conditions also apply.

Please note that any available PhD studentships will be allocated on a competitive basis across a number of projects currently being advertised by the School.

A small number of international awards will be available for allocation across the School. An international award is not guaranteed to be available for this project, and competition across the School for these awards will be highly competitive.

Academic Requirements:

The minimum academic requirement for admission is normally an Upper Second Class Honours degree from a UK or ROI Higher Education provider in a relevant discipline, or an equivalent qualification acceptable to the University.

Project Summary
Supervisor

Zheng Li

More Information

zheng.li@qub.ac.uk

Research Profile


Mode of Study

Full-time: 3 or 3.5 years


Funding Body
Funding TBC
Apply now Register your interest

Computer Science overview

The School of Electronics, Electrical Engineering and Computer Science (EEECS) aims to enhance the way we use technology in communication, data science, computing systems, cyber security, power electronics, intelligent control, and many related areas.

You’ll be part of a dynamic doctoral research environment and will study alongside students from over 40 countries world-wide.

We supervise students undertaking research in key areas of computer science, including:

- Artificial Intelligence
- Cybersecurity
- Computing Systems
- Power Electronics
- Robotics
- Sensor-based Systems
- Wireless Communications

Within the School we have a number of specialist research centres. As part of a lively community of over 100 full-time and part-time research students you’ll have the opportunity to develop your research potential in a vibrant research community that prioritises the cross-fertilisation of ideas and innovation in the advancement of knowledge.

Many PhD studentships attract scholarships and top-up supplements. PhD programmes provide our students with the opportunity to acquire an extensive training in research techniques.

Computer Science Highlights
Professional Accreditations
  • ECIT brings together, in one building, internationally recognised research groups specialising in key areas of advanced digital and communications technology.
Industry Links
  • Queen’s researchers have strong links with the local industry, which boasts a rich mix of local startups and multi-nationals. Belfast is the second fastest growing region in the UK in terms of Knowledge Economy activity (Northern Ireland Economy Report, 2018).
  • CSIT brings together research specialists in complementary fields such as data security, network security systems, wireless-enabled security systems, intelligent surveillance systems; and serves as the national point of reference for knowledge transfer in these areas.
World Class Facilities
  • The state-of-the-art £14m Computer Science Building and the Institute of Electronics, Communications and Information Technology offer bespoke research environments.

    The Institute of Electronics, Communications and Information Technology (ECIT), with state-of-the-art technology, offers a bespoke research environment.
Internationally Renowned Experts
  • You will be working under the supervision of leading international academic experts.
Key Facts

Research students are encouraged to play a full and active role in relation to the wide range of research activities undertaken within the School and there are many resources available including:

  • A wide range of personal development and specialist training courses offered through the Personal Development Programme
  • Access to the Queen's University Postgraduate Researcher Development Programme
  • Office accommodation with access to computing facilities and support to attend conferences for full-time PhD students

Course content

Research Information

Associated Research
Research within the School is organised into research themes combining strengths by working together on major projects, in many cases in collaboration with key technology companies.
ECIT brings together internationally recognised research groups specialising in key areas of advanced digital and communications technology.

PhD Opportunities
PhD Opportunities are available in a wide range of computer science subjects, aligned to the specific expertise of our PhD supervisors.

Research Impact
Queen’s is a leader in commercial impact and one of the five highest performing universities in the UK for intellectual property commercialisation. We have created over 80 spin-out companies. Three of these -
Kainos, Andor Technology and Fusion Antibodies - have been publicly listed on the London Stock Exchange.

Research Projects
Queen’s has strong collaborative links with industry in Northern Ireland, and internationally. It has a strong funding track record with EPSRC and the EC H2020 programme.

Research Success
The research profile produced by the 2014 UK Research Excellence Framework (REF) graded 80 per cent of our research activity as 'world-leading' or 'internationally excellent', confirming the School's reputation as an internationally-leading department.

Career Prospects

Introduction
For further information on career opportunities at PhD level please contact the Faculty of Engineering and Physical Sciences Student Recruitment Team on askEPS@qub.ac.uk. Our advisors - in consultation with the School - will be happy to provide further information on your research area, possible career prospects and your research application.

People teaching you




Course structure
There is no specific course content as such. You are expected to take research training modules that are supported by the School which focus on quantitative and qualitative research methods. You are also expected to carry out your research under the guidance of your supervisor.

Over the course of study you can attend postgraduate skills training organised by the Graduate School.

You will normally register, in the first instance, as an ‘undifferentiated PhD student’ which means that you have satisfied staff that you are capable of undertaking a research degree. The decision as to whether you should undertake a PhD is delayed until you have completed ‘differentiation’.

Differentiation takes place about 8-9 months after registration for full time students and about 16-18 months for part time students: You are normally asked to submit work to a panel of up two academics and this is followed up with a formal meeting with the ‘Differentiation Panel’. The Panel then make a judgement about your capacity to continue with your study. Sometimes students are advised to revise their research objectives or to consider submitting their work for an MPhil qualification rather than a doctoral qualification.

To complete with a doctoral qualification you will be required to submit a thesis of approx 80,000 words and you will be required to attend a viva voce [oral examination] with an external and internal examiner to defend your thesis.

A PhD programme runs for 3-4 years full-time or 6-8 years part-time. Students can apply for a writing up year should it be required.

The PhD is open to both full and part time candidates and is often a useful preparation for a career within academia or consultancy.

Full time students are often attracted to research degree programmes because they offer an opportunity to pursue in some depth an area of academic interest.

The part time research degree is an exciting option for professionals already working in the education field who are seeking to extend their knowledge on an issue of professional interest. Often part time candidates choose to research an area that is related to their professional responsibilities.

If you meet the Entry Requirements, the next step is to check whether we can supervise research in your chosen area. We only take students to whom we can offer expert research supervision from one of our academic staff. Therefore, your research question needs to engage with the research interests of one of our staff.
Assessment

- Assessment processes for the Research Degree differ from taught degrees. Students will be expected to present write up their work at regular intervals to their supervisor who will provide written and oral feedback; a formal assessment process takes place annually.

This Annual Progress Review requires students to present their work in writing and orally to a panel of academics from within the School. Successful completion of this process will allow students to register for the next academic year.

The final assessment of the doctoral degree is both oral and written. Students will submit their thesis to an internal and external examining team who will review the written thesis before inviting the student to orally defend their work at a Viva Voce.

Feedback

- Supervisors will offer feedback on the research work at regular intervals throughout the period of registration on the degree.

Facilities

Full time PhD students will have access to a shared office space and access to a desk with personal computer and internet access.

Entrance requirements

Graduate
The minimum academic requirement for admission to a research degree programme is normally an Upper Second Class Honours degree from a UK or ROI HE provider, or an equivalent qualification acceptable to the University. Further information can be obtained by contacting the School.

International Students

For information on international qualification equivalents, please check the specific information for your country.

English Language Requirements

Evidence of an IELTS* score of 6.0, with not less than 5.5 in any component or equivalent qualification acceptable to the University is required (*taken within the last 2 years).

International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.

If you need to improve your English language skills before you enter this degree programme, INTO Queen's University Belfast offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.

Tuition Fees

Northern Ireland (NI) 1 TBC
Republic of Ireland (ROI) 2 TBC
England, Scotland or Wales (GB) 1 TBC
EU Other 3 £25,600
International £25,600

1 EU citizens in the EU Settlement Scheme, with settled or pre-settled status, are expected to be charged the NI or GB tuition fee based on where they are ordinarily resident, however this is provisional and subject to the publication of the Northern Ireland Assembly Student Fees Regulations. Students who are ROI nationals resident in GB are expected to be charged the GB fee, however this is provisional and subject to the publication of the Northern Ireland Assembly student fees Regulations.

2 It is expected that EU students who are ROI nationals resident in ROI will be eligible for NI tuition fees. The tuition fee set out above is provisional and subject to the publication of the Northern Ireland Assembly student fees Regulations.

3 EU Other students (excludes Republic of Ireland nationals living in GB, NI or ROI) are charged tuition fees in line with international fees.

All tuition fees quoted are for the academic year 2021-22, and relate to a single year of study unless stated otherwise. Tuition fees will be subject to an annual inflationary increase, unless explicitly stated otherwise.

More information on postgraduate tuition fees.

Computer Science costs

There are no specific additional course costs associated with this programme.

Additional course costs

All Students

Depending on the programme of study, there may also be other extra costs which are not covered by tuition fees, which students will need to consider when planning their studies . Students can borrow books and access online learning resources from any Queen's library. If students wish to purchase recommended texts, rather than borrow them from the University Library, prices per text can range from £30 to £100. Students should also budget between £30 to £100 per year for photocopying, memory sticks and printing charges. Students may wish to consider purchasing an electronic device; costs will vary depending on the specification of the model chosen. There are also additional charges for graduation ceremonies, and library fines. In undertaking a research project students may incur costs associated with transport and/or materials, and there will also be additional costs for printing and binding the thesis. There may also be individually tailored research project expenses and students should consult directly with the School for further information.

Bench fees

Some research programmes incur an additional annual charge on top of the tuition fees, often referred to as a bench fee. Bench fees are charged when a programme (or a specific project) incurs extra costs such as those involved with specialist laboratory or field work. If you are required to pay bench fees they will be detailed on your offer letter. If you have any questions about Bench Fees these should be raised with your School at the application stage. Please note that, if you are being funded you will need to ensure your sponsor is aware of and has agreed to fund these additional costs before accepting your place.

How do I fund my study?

1.PhD Opportunities

Find PhD opportunities and funded studentships by subject area.

2.Funded Doctoral Training Programmes

We offer numerous opportunities for funded doctoral study in a world-class research environment. Our centres and partnerships, aim to seek out and nurture outstanding postgraduate research students, and provide targeted training and skills development.

3.PhD loans

The Government offers doctoral loans of up to £26,445 for PhDs and equivalent postgraduate research programmes for English- or Welsh-resident UK and EU students.

4.International Scholarships

Information on Postgraduate Research scholarships for international students.

Funding and Scholarships

The Funding & Scholarship Finder helps prospective and current students find funding to help cover costs towards a whole range of study related expenses.

How to Apply

Apply using our online Postgraduate Applications Portal and follow the step-by-step instructions on how to apply.

Find a supervisor

If you're interested in a particular project, we suggest you contact the relevant academic before you apply, to introduce yourself and ask questions.

To find a potential supervisor aligned with your area of interest, or if you are unsure of who to contact, look through the staff profiles linked here.

You might be asked to provide a short outline of your proposal to help us identify potential supervisors.

Download Postgraduate Prospectus