Data mining and efficiency analysis of Higher Education with a focus on quality and social equity

Department: College of Business and Social Sciences

Contract Type: Fixed Term

Basis: Full Time

Closing Date: Thursday 24^th April 2025 23.59 (UK time)

Supervisor: Dr Akram Dehnokhalaji, Dr Viktor Pekar & Prof Helen Higson

Applications are invited for a three-year PhD studentship, supported by the College of Business and Social Sciences to be undertaken within Aston Business School at Aston University.

The position is available to start in October 2025.

Financial Support

This studentship includes a bursary to cover the tuition fees and an annual maintenance allowance for living costs. 

Background to the Project

We are excited to announce a PhD opportunity focusing on the application of Data Mining and Efficiency Analysis techniques to assess the performance of universities in the UK, with a particular emphasis on Knowledge creation quality and societal impact. This project aims to transform the way universities are evaluated by integrating economic efficiency with key dimensions of educational quality and social equity, addressing the growing demand for more inclusive and sustainable higher education systems.

Project Overview:

This research will explore the factors driving efficiency in universities and develop innovative models for benchmarking performance. By integrating advanced techniques such as Data Envelopment Analysis (DEA), clustering methods, and predictive analytics, the project will assess how well universities are creating high-quality knowledge while meeting the broader social needs of society. The successful candidate will contribute to developing new frameworks that evaluate university performance beyond traditional measures like cost reduction and enrolment growth, prioritizing social mobility, inclusivity, and sustainability.

Key Research Questions:

1. What are the key drivers of efficiency in universities that contribute to high-quality knowledge creation and societal impact?
2. How can a robust DEA model be constructed to evaluate these dimensions and develop actionable target-setting frameworks for universities?

Methodology: The research employs a multi-step methodology, combining descriptive, predictive, and prescriptive analytics:

• Data Collection & Review: Analyse existing literature, assess DEA models, and compile data from multiple higher education secondary data sources such as HESA, and Office of Students.
• Exploratory Data Analysis: Use statistical methods to explore and identify key efficiency factors.
• Model Development & Benchmarking: Apply clustering techniques to group universities and develop advanced DEA models to measure efficiency (e.g., Network DEA, bootstrapping) and equity dimensions.

Candidate Profile:

We are looking for a highly motivated and analytical PhD candidate with a strong background in Operations Research, Business Analytics, Data Science, mathematics, Statistics (or related disciplines). The candidate should be comfortable working with large datasets, applying advanced statistical methods, and developing computational models with prior programming experience (Python, R, etc) is required.

Experience with Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA) would be an advantage.

This is an excellent opportunity for a PhD student to make a meaningful impact in the field of higher education, developing innovative methods to assess and improve university performance while promoting equity and inclusivity. If you are interested in contributing to this pioneering research and advancing our understanding of efficiency and equity in higher education, we encourage you to apply.

Person Specification

The successful candidate should hold a Masters degree in Operations Research, Business Analytics, Data Science, mathematics, Statistics (or related disciplines) with a Merit overall (or equivalent) with a dissertation/research element, PLUS a First or Upper Second Class Honours degree (or an equivalent qualification from an overseas institution).

Contact information

For formal enquiries about this project please contact Dr Akram Dehnokhalaji [email protected].

Submitting an application

Your application must include:

1. English language copies of the transcripts and certificates for all your higher education degrees, including any Bachelor degrees.
2. A Research Statement detailing your understanding of the research area, how you would approach the project, and a brief review of relevant literature. Be sure to use the title of the research project you are applying for. There is no set format or word count.
3. A personal statement which outlines any further information which you think is relevant to your application, such as your personal suitability for research, career aspirations, possible future research interests, and further description of relevant employment experience. 
4. Two academic referees who can discuss your suitability for independent research. References must be on headed paper, signed and dated no more than 2 years old. At least one reference should be from your most recent University. You can submit your references at a later date if necessary.
5. Evidence that you meet the English Language requirements. If you do not currently meet the language requirements, you can submit this at a later stage.
6. A copy of your passport. Where relevant, include evidence of settled or pre-settled status.

Apply for this position here

Alternatively, apply here

If you require further information about the application process, please contact the Postgraduate Admissions team at [email protected]