About the Project
Overview
Micro-expressions are tiny, involuntary facial movements that can occur when a person tries to hide an emotion, but are difficult to analyse because they are subtle, short-lived, and easily confused with ordinary facial movement. While many methods have been developed to recognise and localise micro-expressions, these results remain difficult to understand by people and lack interpretable evidence.
We are looking for candidates to research computer vision, machine learning, and modern vision-language models to create new methods of analysing micro-expressions. Rather than only predicting a label, the proposed models will be designed to identify where the relevant facial evidence occurs, describe what subtle change has been observed, and explain why a prediction has been made.
The project will deliver new methods, benchmark protocols, and evaluation frameworks for explainable and trustworthy micro-expression analysis, with relevance to human-centred AI, and healthcare-related affect analysis. The core novelty of the project is to shift micro-expression research from predominantly vision-only pipelines towards multimodal foundation-model approaches that combine subtle visual motion with structured language-level representations such as action units, temporal descriptions, prompt templates, and evidence-based explanations.
The successful candidate will benefit from training facilities at Manchester Met, and the potential to work with external industry stakeholders.
Objectives
Aim: We will investigate whether vision-language models (VLMs) can improve micro-expression analysis by combining video understanding with language-based reasoning.
- Process micro-facial expression data more efficiently in computer vision and vision language models.
- Create a language-guided representation for subtle facial motion, exploring multimodal data
- Create a spot-then-recognise approach to detect micro-expression intervals and interpret language-aware recognition.
- Generalise and efficiently adapt across different datasets and in-the-wild data.
- Evaluate novel methods and validate against the state-of-the-art in a real-world setting.
Candidate requirements
Candidates must have strong motivation for research and excellent programming skills. Expertise in developing computer vision and machine learning algorithms. Vision Language Model (VLM) experience is desirable. The candidate must be highly motivated and enthusiastic about advancing AI in micro-facial expression analysis and affective computing.
Qualifications
- A high-grade undergraduate degree (first class or upper second) in computer science or MSc in related field.
Skills
- Knowledge of programming, computer vision, machine learning, or related discipline.
- Excellent written and verbal communication skills.
- Experience with Python and relevant AI/ML libraries (such as PyTorch, TensorFlow).
- Ability to work independently and collaboratively within a multidisciplinary team.
- Demonstrated knowledge of multimodal data processing (such as vision, language, 3D).
Funding
These are doctoral teaching assistant positions that combine a PhD programme with a university teaching contract. Your time will be split approximately 60% on research and 40% on teaching. This provides excellent preparation for candidates considering an academic career at a university. The teaching component will typically run over the 22 teaching weeks per year and the 4 assessment weeks. You will help deliver an outstanding student experience by supporting lead academics with classroom and lab teaching and assessment, further building the skills developed within your PhD research programme.
The position is grade 6 with a current salary of £31,236 and includes payment of home PhD tuition fees for the duration of the 6-year award. Home students can apply. Applicants must have the right to work in the UK. We are unable to offer visa sponsorship for this role.
How to apply
The School of Computing and Mathematics is inviting applications for eight independent doctoral projects, with five funded Doctoral Teaching Assistant positions available. All applications will go through an initial review stage conducted by the project supervisors. Candidates selected from this stage will be invited to an interview, where final funding decisions will be made based on performance across all projects.
If you have any questions, contact the principal supervisor, Dr Adrian Davison.
To apply you will need to complete the online application form for a part time PhD in Computing & Digital Technology.
Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest.
Please upload these documents in the supporting documents section of the University’s Admissions Portal or send them to the PGR Admissions team at pgradmissions@mmu.ac.uk.
Please quote the reference: SciEng-DTA Jan 2027-AD-Micro Expression Vision
Application link
PhD Computing and Digital Technology — six years part-time
Funding Notes
These are doctoral teaching assistant positions that combine a PhD programme with a university teaching contract. Your time will be split approximately 60% on research and 40% on teaching. This provides excellent preparation for candidates considering an academic career at a university. The teaching component will typically run over the 22 teaching weeks per year and the 4 assessment weeks. You will help deliver an outstanding student experience by supporting lead academics with classroom and lab teaching and assessment, further building the skills developed within your PhD research programme.
The position is grade 6 with a current salary of £31,236 and includes payment of home PhD tuition fees for the duration of the 6-year award. Home students can apply. Applicants must have the right to work in the UK. We are unable to offer visa sponsorship for this role.
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