Research Fellow in Machine Listening

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Research Fellow in Machine Listening

University of Surrey
Country of Position: 
United Kingdom
Contact Name: 
Mark Plumbley
Subject Area: 
Speech and Language Processing
Signal Processing Theory and Methods
Multimedia Signal Processing
Machine Learning for Signal Processing
Audio and Acoustic Signal Processing
Digital Signal Processing
Start Date: 
April 12, 2018
Expiration Date: 
May 02, 2018
Position Description: 

Salary: GBP 30,688 to GBP 38,833 per annum
Closing Date: 1 May 2018 (23:00 BST)

Applications are invited for a Research Fellow in Machine Listening to work full-time on an EPSRC-funded project "Making Sense of Sounds", to start as soon as possible, for 9.75 months until 13 March 2019. This project is investigating how to make sense from sound data, focussing on how to allow people to search, browse and interact with sounds. The candidate will be responsible for investigating and developing machine learning methods for analysis of everyday sounds, leading to new representations to support search, retrieval and interaction with sound.

The successful applicant is expected to have a PhD or equivalent in electronic engineering, computer science or a related subject, and is expected to have significant research experience in audio signal processing and machine learning. Research experience in one or more of the following is desirable: deep learning; blind source separation, blind de-reverberation, sparse and/or non-negative representations, audio feature extraction.

The project is being led by Prof Mark Plumbley in the Centre for Vision Speech and Signal Processing (CVSSP) at the University of Surrey, in collaboration with the Digital World Research Centre (DWRC) at Surrey, and the University of Salford. The postholder will be based in CVSSP and work under the direction of Prof Plumbley and Co-Investigators Dr Wenwu Wang and Dr Philip Jackson. For more about the project see:

CVSSP is an International Centre of Excellence for research in Audio-Visual Machine Perception, with 125 researchers, a grant portfolio of £20M. The Centre has state-of-the-art acoustic capture and analysis facilities enabling research into audio source separation, music transcription and spatial audio. Audio-visual compute includes 700 cores and a 50GPU machine learning cluster with 500TB of online storage.

Informal enquires are welcome, to: Prof Mark Plumbley (, Dr Wenwu Wang (, or Dr Philip Jackson (

For more information and to apply online, please visit:

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