Responsible Generative AI for Preventative Health Behaviour Change

About the Project

Are you ready to be at the forefront of AI innovation and redefine how Generative AI can support real-world health behaviour change? Join us on a cutting-edge project investigating how adaptive and explainable conversational AI systems can support smoking cessation and long-term behaviour change in public-sector health contexts.

This PhD studentship is 36-month funded through the Research Excellence Awards (REA) within the John Anderson Research Studentship Scheme (JARSS). You will be based in the Department of Computer and Information Sciences at the University of Strathclyde, working in close collaboration with West Dunbartonshire Health and Social Care Partnership (HSCP).

About the Project

Smoking remains one of the leading causes of preventable illness and premature mortality, particularly among individuals living with long-term health conditions. In areas such as West Dunbartonshire, smoking prevalence significantly exceeds the national average, with the highest rates observed in communities experiencing socioeconomic deprivation.

Despite the availability of evidence-based cessation services, sustained behaviour change remains difficult to achieve. Many individuals face barriers including limited access to services, competing life pressures, and the role of smoking as a coping mechanism for stress and mental health challenges. Digital tools have been proposed to extend support, but most existing systems rely on static content or rule-based interactions, which fail to adapt to users’ changing needs over time.

Recent advances in Generative AI and large language models (LLMs) offer new opportunities for personalised, adaptive support through conversational systems. However, their use in health behaviour change remains underexplored, particularly in terms of long-term effectiveness, trust, explainability, and alignment with public-sector constraints.

This project will investigate how responsible, adaptive, and explainable Generative AI systems can be designed and evaluated to support sustained smoking cessation. Working closely with HSCP, the research will be grounded in real-world service contexts, ensuring both practical relevance and societal impact.

Why This PhD Is Your Opportunity to Innovate

RAG models are transforming the AI landscape by combining powerful Large Language Models (LLMs) with external information retrieval mechanisms to deliver more accurate and context-aware responses. These models are reshaping industries such as technology, healthcare, and education. However, RAG models also inherit biases not only from their pre-trained LLMs but also from the external information they retrieve, creating challenges in ethics, fairness, and trust.

Generative AI is transforming how we interact with digital systems, but its role in supporting long-term human behaviour change remains a major open challenge.

Imagine a conversational AI system that:

• Adapts to a user’s motivation, relapse risk, and personal context over time
• Provides support that evolves with the user rather than remaining static
• Explains its reasoning in a way that builds trust and understanding
• Supports individuals in developing lasting coping strategies, rather than creating dependency

What You Will Do

You will design and evaluate innovative approaches for adaptive and explainable Generative AI systems for health behaviour change, contributing to the next generation of AI-enabled public health interventions.

Key Objectives:

• Develop conversational AI systems that provide adaptive smoking-cessation support over time
• Integrate behavioural state modelling (e.g. motivation, relapse risk) into Generative AI systems
• Investigate how different forms of explainability influence user trust, understanding, and engagement
• Design systems that align with public-sector requirements, including transparency, auditability, and data minimisation
• Evaluate system performance in real-world community health settings compared to static or non-adaptive interventions
• Develop methods to assess progressive autonomy, ensuring systems support long-term capability rather than dependency

What We are Looking For

We are seeking ambitious and curious researchers who want to push the boundaries of AI and create meaningful societal impact.

Essential Skills:

• A 2:1 Honours degree or Master’s degree in Computer Science, AI, Data Science, or a related field
• A strong background in machine learning, AI, or data analysis
• Proficiency in programming and model development (e.g. Python)
• Excellent written and oral communication skills
• An understanding of experimental design and evaluation

Desirable Skills:

• Experience with generative AI or conversational systems
• Interest in digital health, behaviour change, or human-centred AI
• Familiarity with explainable AI or responsible AI frameworks
• Experience working with interdisciplinary teams or applied research contexts
• Interest in public-sector or real-world deployment of AI systems

How to Apply:

Applications will be processed on a 'first come, first served' basis, and the hiring process will conclude as soon as a suitable candidate is identified. Interested candidates should email Dr Yashar Moshfeghi (yashar.moshfeghi@strath.ac.uk) and include detailing contact information, and motivation, or background and attach an up-to-date CV.

We are committed to inclusion across race, gender, age, religion, identity, and experience, and we believe that diversity makes us stronger by bringing in new ideas and perspectives. The University of Strathclyde was established in 1796 as “the place of useful learning”. This remains at the forefront of our vision today for Strathclyde to be a leading international technological university that makes a positive difference in the lives of its students, society and the world. Strathclyde was the first institute to win the coveted Times Higher Education “University of the Year” award twice, in 2012 and 2019, and has since been voted the Scottish University of the Year in 2020.

Funding Notes

All home and international students are eligible to apply which will cover the full stipend and tuition fees at the home rate (not the international rate). It includes:

• A fee waiver equivalent to the Home rate; and
• A tax-free stipend of approx. £22,442 p.a. for a maximum of four years and does not need to be paid back. This amount will increase every year, typically with inflation.

International students are permitted to self-fund the difference between the home and international fee rates.

We also welcome self-funded or externally funded applications.