Artificial Intelligence for Healthcare: Generative AI and Trustworthy Machine Learning for Early Disease Detection and Clinical Decision Support

About the Project

Artificial Intelligence (AI) is transforming healthcare by enabling earlier disease detection, improving diagnostic accuracy, and supporting clinical decision-making. Recent advances in Generative AI, Machine Learning, Deep Learning, and Large Language Models (LLMs) offer significant opportunities to analyse complex healthcare data and provide personalised, data-driven insights. However, challenges related to explainability, fairness, trust, and responsible deployment continue to limit the widespread adoption of AI in healthcare.

This PhD project aims to develop and evaluate innovative Generative AI and Trustworthy Machine Learning approaches for early disease detection and clinical decision support. The successful candidate will investigate how AI can be used to analyse healthcare data, generate clinically meaningful insights, and support healthcare professionals in making informed decisions.

The research may involve the use of electronic health records, clinical notes, laboratory results, medical imaging, and other healthcare data sources. A key focus will be the development of AI systems that are accurate, explainable, transparent, fair, and trustworthy. The project will explore topics such as Explainable AI (XAI), Human-AI Collaboration, Clinical Decision Support Systems, Disease Risk Prediction, Responsible AI, and Multimodal AI for healthcare applications.

The successful applicant will work at the intersection of Artificial Intelligence, Data Science, Digital Health, Health Informatics, and Healthcare Innovation. The project offers opportunities for interdisciplinary collaboration and the potential to contribute to real-world healthcare challenges, including chronic disease management, cancer detection, cardiovascular health, and preventive medicine. This PhD provides an exciting opportunity to contribute to cutting-edge research in AI for Healthcare and develop next-generation technologies that support improved patient outcomes, personalised healthcare, and evidence-based clinical decision-making.

Eligibility / Candidate Profile:

Candidates are expected to hold, or be close to completing, a minimum Upper Second-Class Honours degree (2:1) or equivalent in a relevant subject area, such as Computer Science, Informatics, Artificial Intelligence, Machine Learning, Data Science, Health Informatics, Biomedical Engineering, or a closely related discipline. A master’s degree (MSc, MEng, MA, or equivalent) and/or relevant professional or research experience in a related field is highly desirable. Applicants from other academic or professional backgrounds will also be considered, provided they can demonstrate relevant expertise aligned with the research theme.

How to apply

Formal applications can be made via the University of Bradford web site; applicants will need to register an account, select 'Postgraduate Research' as the course and then use the keywords 'computer science'. Applicants should then specify the project title in the 'Research Proposal' section.