Responsible AI for Health and Social Care and Wellbeing

About the Project

The increasing generation, adoption and deployment of Artificial Intelligence (AI) technologies that could impact humanity raise continuously concerns from general public, regulatory bodies and industry. Issues regarding bias, trust, fairness, reproducibility and transparency in data-driven and automated decision support are still challenged to be consistently measured and validated for risk and effectiveness.

This research theme of Responsible AI for Wellbeing (including health care and social care) explores contributions to knowledge and solutions to propose, define, characterise, evaluate, test and validate agentic and generative AI algorithms, building on our renowned expertise in machine learning, explainable AI, big data and AI model governance and their applications. Quantitative and qualitative measures will encompass Explainability, Efficiency, Efficacy, Ethics, Fairness, Reliability, Robustness and Trustworthiness in data, reinforcement learning and machine learning approaches among foundational Responsible AI concepts. The project also explores their validation through a number of case studies for health and social care including pre-, and post-pandemic (e.g. Post-COVID) challenges. These will help understanding and developing valuable personalised reliable responsible AI systems for ethical and deontological benefit of personal users and wider communities.

The multidisciplinary research theme will involve a selection of topics to be confirmed on a personal basis, expertise and expression of interest in problem solving with computational intelligence, AI and Machine Learning, Big Data Science and Technology, Mathematics, Statistics, Logic, Set, Probability Theories, Philosophy (e.g. Ethics), Health and Social Care, Bioinformatics, Economics to assess data and AI models and resources.

What we offer:

As a successful candidate, you will be based in the School of Computer Science, AI & Electronics of the University of Bradford. The PhD students join our dynamic and motivated Artificial Intelligence Research (AIRE) Group comprising of PhD and taught students and interns, postdoctoral researchers, and research active academic staff.

The AIRE group and leader have a renowned and long-standing research knowledge and expertise in fundamental research, collaborative successful contributions to knowledge and applications, and international networking and exchanges. You will also benefit of successful Turing University Network membership environment, and opportunities abroad through Turing Scheme placements.

You will have the opportunity to present your work at relevant conferences and research events; publish contributions in scientific journals; participate in academic and industry activities, and build your research expertise with a highly knowledgeable and friendly academic research team. The University of Bradford is offering a comprehensive and highly supportive doctoral training environment. The University of Bradford is a major BD25 partner of Bradford 2025 UK City of Culture.

Eligibility/ Candidate Profile:

Candidates are expected to hold (or be about to obtain) a minimum 2:1 Hons degree (or equivalent) in a related area / subject, e.g. Computer Science, Data Science, Informatics/Information Science, Big Data, AI, IoT, Mathematics, Statistics, Physics, Philosophy. MSc, MEng, MA or relevant experience in a related discipline is highly desirable. Other academic and career background will be analysed based on specific expertise relevant to this research theme.

How to apply

Formal applications can be submitted via the University of Bradford web site. Applicants should register an account, select 'Postgraduate Research' as the course type and use the keywords 'computer science'. Please include the project title on the Research Proposal section; applicants are not required to supply a research proposal for this project.

Informal enquiries are also welcome.

Funding Notes

This is a self-funded PhD project; applicants will be expected to pay their own fees or have a suitable source of third-party funding. UK students may be able to apply for a Doctoral Loan from Student Finance for financial support.