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Postgraduate research project

Improving the efficiency of adult auditory rehabilitation through automation and machine learning

Funding
Competition funded View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree
View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date

About the project

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.

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