PhD: Sound and Music Processing in Dementia

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  • PhD
  • Sheffield
  • £21,805 p.a. tax-free stipend (increases annually), plus fees and £16,400 research fund

Website sheffielduni The University of Sheffield

Closing date: 11th January

 

The University of Sheffield offers a funded PhD examining how people living with dementia process sound and music in noisy social spaces, and developing technology to reduce sensory overwhelm.


Sound and music processing in dementia (with Age UK Sheffield)

Institution: University of Sheffield, EPSRC Centre for Doctoral Training in Sustainable Sound Futures
Supervisors: Dr Jennifer MacRitchie, Prof Jon Barker
Application deadline: Monday, January 11, 2027
Funding type: Competition Funded PhD Project (Students Worldwide)
Location: Sheffield, United Kingdom
Subject areas: Acoustics, Acoustics Engineering, Biotechnology, Machine Learning, Music, Music Technology, Computer Science, Physics, Psychology

Project Summary

Understanding the perception and embodied experience of sound in dementia is pivotal to designing future support systems that facilitate meaningful community engagement. Advances in machine learning and signal processing techniques offer opportunities to optimise acoustic environments for people living with dementia across different social and musical settings. By personalising auditory experiences and working directly with organisations that support people living with dementia in Sheffield (Age UK Sheffield, JoJanGles music focus group), this research directly targets people more at risk of isolation in a noisier future. Ultimately, this project goes towards ensuring future sound environments are actively engaging and supporting social connection for vulnerable populations.

Project Description

The increasingly noisy environments in the future, intersecting with rising incidences of dementia across the world presents a crucial challenge. A key part of living independently with dementia for longer is the ability to interact with others in public and community spaces. What we see currently throughout the dementia journey is withdrawal from these social spaces, which can often be a result of sensory overwhelm. Sounds intended to induce pleasurable experiences, or to specifically calm and soothe, can instead add to panic, stress and confusion.

Engaging with multisensory experiences and particularly music is accepted as a widely valued experience in dementia, and one that can promote identity, belonging, and general wellbeing. Yet how music and sound are processed in dementia in potentially noisy social spaces is rarely examined, with the bulk of research assuming a hearing typical and cognitively intact population.

The proposed project looks to i) examine sound and music processing within cognitive impairment and ii) to develop technology solutions to reduce sensory overwhelm in social spaces, preserving the ability to interact with sound or music-based programmes. Examining the behavioural responses of people living with dementia to various musical and aural stimuli will identify the acoustic characteristics which are easier or more engaging for an individual. The project will then investigate whether signal processing can adapt the material to better match the individual’s threshold for comfort. This could include personalised predictive overload models which train user-specific machine learning models to evaluate ambient acoustic metrics (e.g. spatial clutter, reverberation, psychoacoustic sharpness) and predict or anticipate stressful auditory situations.

Another approach could involve content-preserving hearable scene processing, i.e. developing real-time acoustic processing for hearables that selectively softens and restructures distressing background soundscapes to create a calmer audio mix without suppressing critical speech, safety cues, or desired musical elements.

Topic Areas: Dementia, Music, Sound, Machine Learning, Computer Science, Technology co-design

Project Partners

The project will be conducted in close collaboration with partners in Sheffield experienced in providing support services to people living with dementia including Age UK Sheffield, and JoJanGles music focus group (a specialized community health activity run by a non-profit health and wellness organization based in Sheffield)

Both partners will offer opportunities to support ongoing dementia services and work directly with people with dementia.

Desired technical skills/academic qualifications/experience

A minimum 2.1 or higher in an undergraduate degree or a relevant master’s degree is required. Applicants with experience or interests in psychology, signal processing or computer science are encouraged to apply. We welcome candidates keen to develop skills across disciplines, and relevant experience need not come only from formal degree study.

We particularly encourage applications from women and other groups under‑represented in research. All appointments will be made on merit.

Mode of attendance

Successful applicants are expected to register as full-time students. However, eligible UK home fees applicants may request to be considered for part-time mode of attendance by the supervisory team.

Sustainable Sound Futures CDT programme

This 4 year PhD project is funded by the Sustainable Sound Futures CDT programme. Details of the application process can be found on https://soundfutures.salford.ac.uk/apply. The successful applicant will join other PhD students across our partner universities (Salford, Bristol, Sheffield and Southampton) as a member of our third CDT cohort and will be actively engaged in our CDT training programme throughout their PhD registration.

Funding Notes

4 year fully funded studentship including

  • Tax Free Stipend – £21,805 per year – increases annually
  • Tuition fees – 4 years
  • £16,400 PhD research fund (conferences, equipment, project materials)
  • Part-time or full-time option available (UK home fees only)

Funding for international students is limited and extremely competitive.

All applications for this project must be submitted via the Sustainable Sound Futures CDT programme website.

To apply for this job please visit www.findaphd.com.