We are currently recruiting a postdoctoral research associate to work on a project entitled “Characterizing the effects of hearing loss and hearing aids on the neural code for music”.
The project is jointly supervised by Prof Nicholas Lesica at the UCL Ear Institute (
lesicalab.com) and Dr. Alinka Greasley at the University of Leeds who leads the Hearing Aids for Music Project (
musicandhearingaids.org).
What’s the problem?
Distorted music perception is a major problem for the hard of hearing and current hearing aids often fail to help. But without a detailed understanding of the auditory processing of music and how it is disrupted by hearing loss, it remains unclear how the benefits of hearing aids for music can be improved. We aim to characterize the neural code that forms the brain’s internal representation of music to identify the features that underlie normal and impaired perception and to develop specific design targets for new hearing aids.
What’s the opportunity?
The project will make use of novel methods for large-scale electrophysiology in animal models of human hearing that we have recently developed (see Armstrong et al., Nat Biomed Eng, 2022). These methods allow us to collect unique datasets containing the activity of hundreds of auditory neurons over many hours. The postholder’s primary duty will be to analyze these datasets to characterize the neural code at both the single neuron and network level and to link the results to the real-world experiences of human listeners based on a large-scale psychoacoustics dataset.
Who are we looking for?
The ideal candidate will have expertise in statistical and machine learning methods for large-scale data analysis and experience applying these methods in the context of music, audio, hearing, and/or neuroscience.
What will you do?
- Build data pipelines for processing large-scale neural activity recordings
- Develop models to analyze the mapping from sounds to neural activity
- Identify the distortions in the neural code that underlie impaired perception
- Design new sound transformations for correcting distortions in the neural code