Developing AI-based equitable risk prediction models for long-term conditions using longitudinal health data

We are recruiting new Doctoral Researchers to our EPSRC-funded Doctoral Landscape Award (DLA) PhD studentships starting 1 October 2025.

Applications are invited for the project title: Developing AI-Based Equitable Risk Prediction Models for Long-Term Conditions Using Longitudinal Health Data.

Successful applicants will receive an annual stipend (bursary) of approximately £21,237, including inner London weighting, plus payment of their full-time home tuition fees for a period of 42 months (3.5 years).

You should be eligible for home (UK) tuition fees there is a very limited number (no more than two) of studentships available to overseas applicants, including EU nationals, who meet the academic entry criteria including English Language proficiency.

You will join the internationally recognised researchers in the Department of Computer Science research and PhD programmes | Brunel University London.

The project

Multiple long-term conditions (MLTC) present significant healthcare challenges, leading to increased service utilisation and expenditure. This project aims to develop robust and explainable AI methods for predicting MLTC risks using health records data, thereby enhancing early risk detection, improving patient care, and optimising healthcare resources.

Some of the suggestive activities are as follows:

Analyse longitudinal electronic health records to prepare data for AI modelling
Design explainable AI models for MLTC risk prediction, emphasising fairness and transparency
Formulating methods for efficient explanations for longitudinal time-series models
Conduct testing, validation and risk assessment of the developed AI to ensure models perform equitably across diverse patient demographics and adhere to ethical standards
Work with healthcare organisations for real-world implementation and iterative improvement

The project will employ advanced data pre-processing techniques and develop novel explainable deep learning algorithms, including transformer-based multistate models to predict risk progression across different demographic groups. Collaboration with healthcare partners will facilitate practical deployment and continuous refinement of the AI models.

Conducted within the Department of Computer Science at Brunel University London under the supervision of Dr. Tahmina Zebin, the project will involve frequent collaboration with colleagues from the Norwich Medical School. This project will provide the PhD student with an opportunity to gain experience in rapidly expanding fields of computer science that include deep machine learning, risk prediction modelling, and digital health.

Please contact Dr Tahmina Zebin at tahmina.zebin@brunel.ac.uk for an informal discussion about the studentships.

Eligibility

Applicants will have or be expected to receive a first or upper-second class honours degree in an Engineering, Computer Science, Design, Mathematics, Physics or a similar discipline. A Postgraduate Masters degree is not required but may be an advantage.

Skills and experience

Applicants will be required to demonstrate the following skills;

A 2:1 technology-related degree (Computer Science or a closely related degree with a strong Data Science and AI component)
Some proficiency in state-of-the-art AI development techniques, with a focus on deep learning, supervised, unsupervised and advanced time series modelling techniques
Strong programming skills, particularly in Python, and experience with popular AI and machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn
Ability to critically evaluate academic literature
A high level of motivation, with the ability to work effectively both independently and as part of a team. Strong collaboration skills and excellent communication abilities are essential

How to apply

There are two stages of the application:

1. Applicants must submit the pre-application form via the following link

https://app.onlinesurveys.jisc.ac.uk/s/brunel/epsrc-dla-25-26-pre-application-form-brunel-university-of-londo

by 4 pm on Friday 17 January 2025.

2. If you are shortlisted for the interview, you will be asked to email the following documentation in a single PDF file to cedps-studentships@brunel.ac.uk within 72 hours.

Your up-to-date CV;
Your undergraduate degree certificate(s) and transcript(s) first or upper-second class honours degree essential;
Your postgraduate master's degree certificate(s) and transcript(s) if applicable
Your valid English Language qualification of IELTS 6.5 overall (minimum 6.0 in each section) or equivalent, if applicable; this must be valid up to 31 October 2025
Contact details for TWO referees, one of which can be an academic member of staff in the College

Applicants should therefore ensure that they have all of this information in case they are shortlisted.

Interviews will take place on 13 and 14 February 2025. For shortlisted international/EU applicants’ interviews will be via Microsoft Teams and for UK applicants’ interviews will be in person at the Brunel University of London campus.

Meet the Supervisor(s)

Tahmina Zebin - Dr. Tahmina Zebin is a Senior Lecturer in Computer Science. Prior to this post, she was a Lecturer in the School of Computing Sciences at the University of East Anglia and has led an On-device and Explainable AI Research Group. She completed her PhD studies in 2017 from the University of Manchester. Following her PhD, Tahmina was employed as a postdoctoral research associate on the EPSRC funded project Wearable Clinic: Self, Help and Care at the University of Manchester and was a Research Fellow in Health Innovation Ecosystem at the University of Westminster. Her research expertise includes Advanced Video and Signal Processing, Explainable and Inclusive AI, Human Activity Recognition, Risk Prediction Modelling from Longitudinal Electronic Health Records using various statistical, machine learning and deep learning techniques.