Department of Electronic and Electrical Engineering, The University of Manchester
Supervisors: Dr J Wijekoon, Prof Hujun Yin
Applications accepted all year round
Competition Funded PhD Project (Students Worldwide)
About the Project
Human behaviour and emotional states are complex and can change subtly over time. Facial expressions, voice, eye movements and other behavioural cues can provide valuable information about how a person is feeling and interacting with the world around them. However, many of these changes are difficult to identify consistently through observation alone.
This project aims to develop an innovative artificial intelligence (AI)-based system that can analyse multiple behavioural signals, including facial expressions, micro-expressions, vocal characteristics and eye-related behaviour, to improve our understanding of human behaviour and emotional states.
A particular focus of the research will be on applications that could support the assessment and long-term monitoring of individuals with autism. People with autism can experience differences in communication, emotional expression and social interaction, and these characteristics can vary considerably between individuals and over time. Developing objective, technology-based approaches could provide additional information to support researchers, clinicians and other professionals in understanding these individual differences.
The project will investigate how AI can combine information from different sources to identify subtle behavioural patterns that may not be readily apparent from any single signal. The research will also explore efficient computing approaches that could enable these technologies to operate reliably and, in the longer term, support practical real-world applications.
The project has the potential to contribute to the development of more objective, personalised and technology-enabled approaches to understanding human behaviour and emotional wellbeing. In the longer term, such technologies could help support earlier identification of meaningful behavioural changes, improve monitoring over time, and provide additional evidence to complement existing professional assessment and support.
The research will bring together expertise in artificial intelligence, signal processing, computer vision, speech and behavioural analysis, and electronic system design. By combining these areas, the project aims to develop new technologies that can contribute to improved understanding of human behaviour and ultimately support better outcomes for individuals, families and healthcare professionals.
This project is expected to start in September 2027.
Before you apply: We strongly recommend that you contact the supervisors for this project before you apply.
How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Engineering Scholarships. If you don't already have an applicant account, please follow the instructions here.
When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing the motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications. Please note late or incomplete applications will not be considered.
Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status.
We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder.
Eligibility: The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree (or international equivalent) in Electrical and Electronic Engineering, Computer Engineering, Computer Science, Artificial Intelligence, Biomedical Engineering, or a closely related discipline OR any upper-second class (2:1) honours degree and a Master's degree at merit (or international equivalent) in Electrical and Electronic Engineering, Computer Engineering, Computer Science, Artificial Intelligence, Biomedical Engineering, or a closely related discipline. Candidates should have a strong interest in AI-based analysis of human behaviour and experience or knowledge in areas such as machine learning, signal processing, computer vision, speech/audio processing, or data analysis. Experience with programming, particularly Python or similar computational tools, would be advantageous. Candidates should demonstrate the ability to undertake interdisciplinary research and a willingness to develop skills in AI, multimodal data analysis and healthcare-related applications. Previous research experience in a relevant area would be desirable but is not essential.
This project will remain open until filled.
If your application is submitted by 1st November 2026, you can expect a decision by 18th December 2026.
If your application is submitted by 15th January 2027, you can expect a decision by 30th March 2027.
Self or externally funded students can also be considered for this project.
FSE_SoE
Funding Notes
Funding for this project covers tuition fees, UKRI minimum annual stipend (currently £21,805/annum) and up to a £2.5k/annum research training support grant for the full duration of the 3.5-year programme.