[Home tuition fees (£5,006/year for 2025/26) covered for three years; international students must pay the difference. Standard UKRI stipend (£20,780 for 2025/26) provided for duration of award.]

This funded PhD studentship at Manchester Metropolitan University offers an exciting opportunity to join the Faculty of Science and Engineering’s vibrant doctoral research community. The project is part of Manchester Met’s AI, Digital and Cyber-Physical Systems research theme, which is dedicated to improving quality of life through cutting-edge technology and impactful research. The focus of this studentship is on designing generalisable, context-aware multimodal learning frameworks to understand and model human behaviours across diverse socio-contexts. Applications of this research include healthcare, emotional recognition, and human-machine interaction, with the aim of advancing personalised care and assistive technologies.

The successful candidate will explore multimodal learning and unlearning techniques using vision, language, and audio signals to build intelligent systems capable of interpreting and responding to human actions and emotions. The project objectives include curating multimodal datasets, developing robust context-aware learning methods, designing unlearning techniques to address bias and privacy concerns, and evaluating the generalisability of these methods across different socio-contexts. Validation will be carried out through two use cases, ensuring real-world relevance and impact.

Funding is available for both Home and International students. Home tuition fees (£5,006/year for 2025/26) are covered for the three-year duration of the award. International students must pay the difference in tuition fees (Band 2 for 2025/26). All students will receive a standard UKRI stipend, currently set at £20,780 for the academic year 2025/26. This financial support enables students to focus on their research and professional development within a collaborative environment, working alongside postdoctoral researchers, early-career academics, and established professors.

Applicants should possess a high-grade undergraduate degree (first class or upper second) in Computer Science or an MSc in a related field. Strong motivation for research, excellent programming skills, and experience in developing computer vision and machine learning algorithms are desirable. Candidates should be enthusiastic about advancing AI for societal impact and have knowledge of programming, computer science, computer vision, machine learning, Python, and relevant AI/ML libraries such as PyTorch and TensorFlow. Demonstrated experience with multimodal data processing (vision, language, audio) and machine learning techniques is expected.

To apply, interested candidates should contact Prof. Moi Hoon Yap for an informal discussion. The formal application process involves completing the online application form for a full-time PhD in Computing & Digital Technology, submitting the Doctoral Project Applicant Form, CV, and a covering letter that maps skills and experience to the project’s aims and objectives. These documents should be uploaded via the University’s Admissions Portal. The application deadline is 31 January 2026, with an expected start date in October 2026. Please quote the reference SciEng-MHY-2026-27-Multimodal Context-Aware Behaviour in your application.