Research Associate in Speech Processing and Machine Learning for Detecting Cognitive Impairment at University of Sheffield

Contract Type: This post is fixed-term with a start date as close as possible to 1st September 2023, and an end date of 31st January 2025.

We are seeking an outstanding Research Associate to work on Speech Processing and Machine Learning for Detecting Cognitive Decline in the Speech and Hearing (SPandH) research group in the Department of Computer Science.

You should have a track record of working with speech processing, speech technology or machine learning in a related field. You should also have demonstrable hands-on experience in the implementation of classification and regression pipelines, as well as the necessary mathematical and machine learning background. Ideally, such a track record is demonstrated by publications in international journals and conferences. Candidates are required to hold a PhD in the field and if appointed, publish results and travel to conferences. Understanding of the challenges of working in a highly interdisciplinary environment is also required.

In this role you will work in the well-connected, world-leading Speech and Hearing (SPandH) research group at the University of Sheffield, which has a reputation for internationally leading research and is one of the largest such groups in Europe. You will also be collaborating with a diverse team of experts in Neurology, Stakeholder engagement, Machine Learning, Health Economy and commercialisation of Healthcare technology in the CcHAT project.

The post holder will join a team of researchers led by Prof Heidi Christensen who is working on the automatic detection of cognitive decline and general processing of pathological speech in SPandH. The team has published widely and works on a number of projects funded by e.g. EPRSC, NIHR and MRC. Christensen is the technical lead of the www.cognospeak.com system which is currently recruiting nationwide and is being trialled in the memory and stroke assessment pathways.

Apply by clicking on the Apply button located near the top of your screen.