|Funding for tuition fees and a living stipend are available on a competitive basis. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
|29th November 2023
|31st August 2024
Project title: Improving the efficiency of adult auditory rehabilitation through automation and machine learning
Supervisory Team: Steven Bell, Thomas Blumensath, Stefan Bleeck
There is a large cost in terms of staff time and devices in supplying hearing aid provision to adults in the UK and a shortage of audiology staff able to deliver services.
Automation and machine learning, for example in terms of automated hearing testing, machine learning to seek information from patients and self-fitting hearing aids have the potential to reduce the staff time required to deliver services and hence to improve access to services. However it is critical to still be responsive to the needs to service users and to be safe.
The aim of this project is to explore which aspects of hearing assessment and hearing aid provision for adults in the UK might be automated. It would develop an understanding of the current care pathway in the UK, identify aspects that might be automated and then explore how that implementation could occur whilst maintaining a high-quality service for the end user. It is also important that any approaches used are considered trustworthy. The intended end point is a set of recommendations for clinical practice with some evidence demonstrating the clinical efficiency of such approaches.
A successful candidate could either be someone with an audiology background who has an interest in machine learning, or someone with a machine learning background with interest in healthcare applications.
The project will be hosted within the Institute of Sound and Vibration Research at the University of Southampton, which is an internationally recognised centre of excellence for research and training in acoustics and audiology. It is unique in bringing together hearing science and engineering within one Institute, with taught programmes in Audiology and Engineering, as well as hosting a Cochlear Implant Centre. It is engaged in fundamental and applied research in hearing science and balance, with research facilities and expertise to support this work.
If you wish to discuss any details of the project informally, please contact Steven Bell Research Group Signal Processing, Hearing and Audio, Email: email@example.com, Tel: +44 (0) 2380 59 4950
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).
Closing date: applications should be received no later than 31 August 2024 for standard admissions, but later applications may be considered depending on the funds remaining in place.
Funding: Funding for tuition fees and a living stipend are available on a competitive basis. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
How To Apply
Apply online: Search for a Postgraduate Programme of Study (soton.ac.uk). Select programme type (Research), 2024/25, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Steven Bell
Applications should include:
Two reference letters
Degree Transcripts/Certificates to date
For further information please contact: firstname.lastname@example.org
Type / Role: