Research Fellow in Acoustic Signal Processing and Machine Learning at University of Surrey
Closing date for applications: 3 January 2021
To build on the expertise within the Centre for Vision, Speech and Signal Processing (CVSSP) we are seeking to appoint a Research Fellow in Acoustic Signal Processing and Machine Learning.
This post is funded by MoD Defence and Security Acceleration (DASA) Programme Phase 2 scheme “Countering Drones”. The project will be led by Prof Wenwu Wang in the Machine Audition Lab of the Centre for Vision Speech and Signal Processing at the University of Surrey. This is a joint project with an industrial partner, aiming to develop AI methods for detecting drone sound using acoustic sensors.
The postholder will be responsible for investigating and developing signal processing and machine learning methods for detecting, localizing and recognizing sound sources from drones, collecting and augmenting the drone dataset. The postholder will be based in CVSSP and work under the direction of PI Prof Wang, in collaboration with an industrial partner.
CVSSP is one of the largest groups of its type in the UK, with over 180 active researchers working in the areas of vision, image processing, medical imaging, and audio, and a grant portfolio of over £20M. The Centre has state-of-the-art acoustic capture and analysis facilities enabling research into audio signal processing, music transcription and spatial audio, and a Visual Media Lab with video and audio capture facilities supporting research in real-time video and audio processing and visualisation. It has an extensive computing infrastructure for audio-visual processing and storage, comprised over 1,000 processing cores and a recent university investment of 600TB of fast, object based storage.
For informal enquiries and further information please contact Professor Wenwu Wang on firstname.lastname@example.org
Further details and application form are here.
For more information and to apply online, please download the further details and click on the ‘apply online’ button above.
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