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PhD Studentship - Self-supervised Learning for Multimodal Emotion Understanding

Manchester Metropolitan University

Qualification Type: PhD
Location: Manchester
Funding for: UK Students
Funding amount: £19,237 (annual stipend of the research council minimum rate for 2024/25)
Hours: Full Time
Placed On: 25th June 2024
Closes: 22nd July 2024

This is a full-time, funded PhD opportunity in the Faculty of Science and Engineering. It is open to both home and overseas students. Please note that only home fees will be covered - eligible overseas students will need to make up the difference in tuition fee funding.

This opportunity provides an annual stipend of the research council minimum rate (set by UKRI) of £19,237 for 2024/25.

Please note that the expected start date for home students is October 2024 and international students January 2025.

Project contact

Dr Xinqi Fan (x.fan@mmu.ac.uk)

Project advert

This studentship is offered as part of wider Manchester Metropolitan University's investment in our future thought leaders, this represents an opportunity to join the Faculty of Science and Engineering’s growing doctoral research community committed to excellent research with impact.

This project forms an exciting research opportunity to join Manchester Met’s AI, Digital and Cyber-Physical Systems theme for improving life quality. Homecare robots are seen as a solution to the challenges posed by the rapidly growing elderly population and increasing healthcare costs.

However, most robots only offer physical assistance and lack emotional support. This project aims to address these limitations by building multimodal emotion understanding methods with an application to human-robot interactions to understand and response to human emotions.

The successful candidate will join the energetic human-centred computing group led by Professor Moi Hoon Yap.

Project aims and objectives

The project aims to design innovative deep multimodal learning methods to understand human emotions. It will address the following key questions:

  • How can large-scale unlabelled videos be effectively utilized?
  • How can privacy concerns from humans be appropriately addressed?
  • How can true emotions be detected when individuals conceal them?
  • How to integrate multimodal emotion understanding algorithms on a robot?

Specific requirements of the project

Candidates must have a strong motivation for research and excellent programming skills. Expertise of developing computer vision and machine learning algorithms would be desirable, with an interest in image analysis.

Qualifications

  • A high-grade undergraduate degree (first class or upper second) in Computer Science or MSc in related field

Skills

  • Knowledge of software development and programming
  • Good communication and writing skills
  • Developing image analysis/machine learning algorithms would be beneficial
  • Able to work as part of a joint team for deep learning and robotics

How to apply

Interested applicants should contact Dr Xinqi Fan (x.fan@mmu.ac.uk) for an informal discussion.

To apply you will need to complete the online application form for a full-time PhD in Computing and Digital Technologies (or download the PGR application form).

You should also complete the PGR thesis proposal and Narrative CV addressing the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area as being of importance and interest. 

If applying online, you will need to upload your statement in the supporting documents section (via the ‘Apply’ button above), or email the application form and statement to PGRAdmissions@mmu.ac.uk

Expected start date: Home students October 2024. International students January 2025.

Please quote the reference: SciEng-XF-2024-Multimodal-Emotion-Understanding

Find out more

Email address: x.fan@mmu.ac.uk

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