PhD Studentship Generative Models for Clinically Relevant Motion Capture

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 Sean Maudsley-Barton (s.maudsley-barton@mmu.ac.uk)

Project advert

This PhD aims to develop generative models for use in the clinical assessment of movement disorders, such as Dementia, Parkinson’s and Delerium. You will be part of a cross-departmental team at the intersection of AI and health as part of the Human Centred Computing theme.

This studentship is offered as part of wider Manchester Metropolitan University 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.  

The lack of data is a major hurdle in using AI in the assessment of movement disorders. Available datasets are small and imbalanced. Hence, the need for generative approaches to augmenting the data. However, standard approaches can produce eery and uncanny outputs. We propose using fundamental neuromuscular signals (EEG, EMG, ROM) to constrain and guide the generative models to produce clinically plausible data

A background in AI is essential, with links to life science, sports science or medicine desirable.  However, training will be provided to the successful candidate by our highly experienced team.

Specific requirements of the project

Essential Criteria:

• Experience in training machine models with at least one of the following (Python, MatLab, R)
• An ability to critique and analyse scientific evidence, methodology and data.
• Strong interpersonal, communication and organisational skills.

Desirable Criteria:

• M.Sc. or Research Masters in a relevant discipline such as mathematics, computer science, data science or statistics.
• Experience with handling EEG and/or EMG data.

How to apply

Interested applicants should contact Dr Sean Maudsley-Barton for an informal discussion.

To apply you will need to complete the online application form for a full-time PhD in Computer Science (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-SMB-2024-generative-models

Find out more

Email address: s.maudsley-barton@mmu.ac.uk

Advert information