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Current vacancies
PhD student – How Generative AI can Create Tipping Points for Psychological and Behavioural Change
Supervisor: Prof Laura G.E. Smith, Department of Psychology, University of Bath.
Description
This is an exciting opportunity for a motivated and talented PhD student to join the human-centered design theme of the Artificial Intelligence for Collective Intelligence (AI4CI) UKRI AI Hub , supervised by Professor Laura Smith (Psychology) and Dr Harish Tayyar Madabushi (Computer Science) at the Department of Psychology, University of Bath.
This project lies at the intersection of psychology, artificial intelligence (AI), and human-computer interaction. We are looking for students who are interested in combining skills in psychology and computer science to investigate how interactions with intelligent agents and their underpinning large language models (LLMs) affect processes such as radicalisation and deradicalisation. This will involve investigating how and why interacting with intelligent agents can affect psychological and behavioural tipping points for communities and for individuals. The lessons learned may be applied to understanding how to mitigate nefarious influence attempts, including exposure to mis/disinformation.
Deadline: 27 April 2025
AI Hub PhD Studentship – Modelling human mobility within Cities and machine learning approaches
Supervisor: Professor Alison Heppenstall, Professor of Geocomputation, University of Glasgow.
Description
Individual-based activity models, such as MATSIM, have experienced significant uptake due to increased data availability and enhanced computational power. However, there is a need for improvement in activity scheduling to achieve a more accurate representation of an individual’s daily activities. This PhD research will explore the use of diverse datasets and machine learning approaches to enhance the representation of daily activities within an individual-level activity model. These will be embedded within an existing MATSIM application to test out a number of potential scenarios within Glasgow, for example, what is the impact of the introduction of congestion charges or reducing capacity on the M8 on accessibility and inequalities within the city?
Deadline: 1 April 2025
PhD Studentship in Defining immunosuppression phenotypes using machine learning
Supervisor: Dr Theresa Smith, Senior Lecturer in Statistics and Deputy Director of the SAMBa Centre for Doctoral Training, University of Bath.
Description
This project will use machine learning techniques to devise more tailored vaccination policies to protect immunosuppressed individuals. Immunosuppression is a heterogenous state, reflecting multiple underlying causes. Different factors (such as kidney disease) may play different roles in infection risk according to the individual context (such as the cause, severity or treatment of the kidney disease). Understanding immunosuppression is critical for managing individual patients’ risk of infection and for policy-makers’ response to epidemics. At present, vaccine policy tends to combine individuals with different types and causes of immunosuppression, or to use checklists of conditions which do not vary according to the individual context.
Deadline: 6 April 2025
PhD Studentship in Machine learning to identify clusters of patients with immune mediated inflammatory illnesses.
Supervisor: Dr Theresa Smith, Senior Lecturer in Statistics and Deputy Director of the SAMBa Centre for Doctoral Training, University of Bath.
Description
This project will use clustering techniques to understand longitudinal multimorbidity patterns in patients with immune-mediated inflammatory diseases (IMIDs). IMIDs are a group of long-term health conditions where inflammation caused by imbalances in the immune system damages the body. IMIDs include rheumatoid arthritis, systemic lupus erythematosus, and psoriatic arthritis. They are associated with higher risk of other health conditions (known as comorbidity or multimorbidity), reduced quality of life, and premature death.
Deadline: 6 April 2025
PhD Studentship in Health applications of Dynamic Bayesian Networks
Supervisor: Dr Theresa Smith, Senior Lecturer in Statistics and Deputy Director of the SAMBa Centre for Doctoral Training, University of Bath.
Description
Bayesian Networks (BNs) are a popular class of models which capture complicated, multivariate relationships through a graphical structure that is interpretable for both statistical and non-statistical users. While BNs are frequently used in health applications, they are often fit to data representing a single snapshot in time and therefore can only detect associations between risk factors and health outcomes. Together with large-scale longitudinal data, casual network models such as Dynamic Bayesian Networks (DBNs) can help us model multivariate temporal trends and identify the casual relationship present among risk factors and health conditions.
In this project, you will explore and develop novel DBN-based methods to find casual relationships with potential applications in a variety of health areas including
- Explainable forecasts of hospital bed capacity
- Personalised predictions from diabetes wearables
- Early warning of disease outbreaks based on wastewater samples
Deadline: 6 April 2025
Future vacancies
Exciting opportunities to pursue PhD research with the AI4CI Hub will be advertised here.
Our interdisciplinary projects are at the cutting edge of AI and Collective Intelligence, providing a unique chance to work alongside leading researchers and stakeholder partners on real-world challenges.
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