phd topics in data science

Last Updated on September 2, 2023

PhD Topics ‍in Data‌ Science

In recent years, data science has emerged as a highly ⁤sought-after ⁤field ​of study. Its relevance and application in various sectors have piqued the interest of both ⁣academics and⁤ industries alike. As a result, many aspiring researchers are considering pursuing a PhD ⁣in data science to delve deeper into‌ this​ evolving ‌discipline. However, choosing an appropriate topic‌ for a PhD in ​data⁤ science ‍can be a daunting​ task.⁢ Therefore, this article aims to shed some ‌light ⁢on potential⁢ areas of research within ⁣the domain of data science.

1. Machine Learning and Artificial Intelligence: With the rapid advancements in technology, machine learning and artificial ‌intelligence have become integral components of data science. A PhD in this field may involve exploring innovative algorithms and techniques for improving machine​ learning models, developing new approaches to deep learning, or investigating

The energy consumption in the building sector has increased steadily due to the use of HVAC systems. As part of energy benchmarking process, the quality and quantity of energy data exploited are important in achieving energy efficiency built environment. With evolve in data science techniques and intelligent energy management, such as control and automation, smart metering, and real-time monitoring, sparse data in new and diverse forms can be exploited by artificial intelligence or machine learning techniques. The use of data science techniques can increase the energy efficiency in the built environment by accurately monitor, collect and store the huge amount of data.

Aim and scope of work

This project aims to develop data-centric energy models for accurate simulations of building energy performance and building energy management. Data science will be used to address the following challenges in the area of building energy management: prediction of energy demand, analysis of building operations, detection of energy consumption patterns and AI & machine learning.


The successful applicant will be from building physics or computing engineering background holding the minimum of a first degree (2:1 or above). Good understanding and prior experience on data science techniques that applied to building energy modelling will be an advantage.

Candidates are requested to submit a more detailed research proposal (of a maximum of 2000 words) on the project area as part of their application.

This is a potential research degree area, subject to the approval of the University. If you are interested in undertaking a research degree in this area, please make contact with the Dean to discuss your proposal.

Data Science & Informaticscovers a wide range of applied and theoretical research. Our research looks at fields including Artificial Intelligence and Machine Learning, through to Data and Information Visualisation.

Data Science has found applications across industry sectors, with business seeking to generate value from data using artificial intelligence and machine learning. The full economic and societal benefits have yet to be reaped. These benefits are enormous, particularly when combined with other emergent technologies such as AR/VR for data driven design and production processes in key industries. Embedding AI across the UK will create thousands of high-quality jobs and drive economic growth.

A recent study found digital technologies including AI created a net total of 80,000 new jobs annually across a population similar to the UK. It is estimated that AI could add £232bn to the UK economy by 2030 (UK Government Industrial Strategy White Paper 2017).

Our application areas of Data Science are aligned with our key strengths in Games and Cyber Security. We are exploring how AI and neural networks can generate content for games, and how data analytics can improve the player experience.

We are also applying state of the art Machine Learning models for intrusion detection systems. Our expertise is broadening its reach into areas including health, community and social care. The majority of our research projects are rooted in client-facing, real-world problems faced by games companies, charities, innovation centres and more.

Our vibrant research culture encourages areas of cross- and inter-disciplinary working. An example of this is a collaboration between psychology and data science where data analytics are applied to understand how people learn through game-based learning.

1. Meet the academic entry requirements

The minimum entry requirement for all our research degrees is an Upper Second Class Honours degree (or equivalent) at undergraduate level in an appropriate discipline and/or a Master’s degree. In some cases, appropriate professional or experiential learning may be considered in combination with a lower classification of Honours degree.

2. Meet the visa and English language requirements

If you’re not from the European Economic Area (EEA) and/or Switzerland, you may need to apply for a visa. You can find out more about applying for a visa and collecting your Biometric Residence Permit (BRP) on our Student Visa page. To identify whether or not you need to apply for a visa, please visit the UKBA website.

If your first language is not English or your undergraduate/Master’s degree was not taught in English, you are also required to hold a suitable English language certificate.

If you require a Student Visa, you must provide one of the following English language certificates:

  • West African at B(4)
  • NECO at B(4)
  • IELTS 6.5 with no band less than 6.0*

If you do not need a Student Visa or are an EEA national, you are permitted to use one of the following:

  • TOEFL 80 with no band less than 18*
  • Pearson’s PTE 61 with no band less than 56*

*The University can only accept these qualifications if they were completed two years prior to the start of the programme.

3. Find a supervisor

You can look for potential supervisors by searching keywords, names or publications in the Staff Explorer. This will ensure that we have appropriate expertise You will also gain an understanding of the prior work of the researcher.

You should consider contacting the potential supervisor to discuss your ideas and the possibility of undertaking a research degree under their supervision. Discussion will also help you tailor your application to suit Abertay’s specific expertise in the area. Ask for feedback and be prepared to take those comments into consideration when finalising your research proposal.

You can also contact the Dean of School or our Graduate School if you would like advice on potential supervisors.

Please avoid vague blanket emails to several potential supervisors as these are unlikely to be successful.

4. Secure funding

 Write your research proposal

This is your opportunity to state your research objectives, to grab the reader’s attention and highlight your suitability for research degree study.

The proposal should be around 6-8 pages in length (including references) and follow the section headings below.

  • Title.
  • Abstract (summary).
  • Introduction/background.
  • Hypotheses, objectives or research question.
  • Proposed methodology.
  • How will you disseminate your findings (pathways to impact).
  • Ethical considerations.
  • Summary and conclusions.
  • References.
  • About you: briefly describe your relevant experience and how it will help you achieve your objectives, explain why you are an excellent candidate for a research degree, and identify your additional professional development and training needs.

Some good practice tips:

  • Be clear and concise.
  • Structure your proposal by breaking up blocks of text into smaller paragraphs (with headings).
  • Reference you work.
  • Justify your objectives.

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