We have a research associate (postdoc) position to work on spatial audio processing and spatial hearing using methods from machine learning. The aim of the project is to design a method for interactively fitting individualised filters for spatial audio (HRTFs) to users in real-time based on their interactions with a VR/AR environment. We will use meta-learning algorithms to minimise the time required to individualise the filters, using simulated and real interactions with large databases of synthetic and measured filters. The project has potential to become a very widely used tool in academia and industry, as existing methods for recording individualised filters are often expensive, slow, and not widely available for consumers.

The role is initially available for up to 18 months, ideally starting on or soon after 1st January 2022 (although there is flexibility). The role is based in the Neural Reckoning group led by Dan Goodman in the Electrical and Electronic Engineering Department of Imperial College. You will work with other groups at Imperial, as well as with a wider consortium of universities and companies in the SONICOM project (€5.7m EU grant), led by Lorenzo Picinali at Imperial.