Research Fellow on Machine Learning for Perceptual Quality Prediction of Spatial Music

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The role

Applications are invited for a Research Fellow (RF) position for 12 months within the Centre for Vision Speech and Signal Processing (CVSSP), University of Surrey, UK, to work on building machine learning and AI models for perceptual quality prediction of spatial music. 

The post is funded by a leading industry partner. The focus will be to develop machine learning and AI models and signal processing algorithms for perceptual quality prediction and rating of songs reproduced using 3D rendering algorithms.  

About you

The post-holder is expected to have a PhD degree (or equivalent) in machine learning, spatial audio, audio signal processing, audio perception, audio quality assessment, or a related area in electronic engineering, computer science, applied mathematics, or statistics. Preference will be given to those who have experience on machine learning/AI, spatial audio, but candidates who have experience in audio perception and signal processing are welcome to apply.  The post-holder is expected to have strong analytical and programming skills in Python, Matlab or C/C++. The post-holder will also collaborate with other team members, such as the Research Fellow who focuses on listening tests and data curation.

The post-holder will be based in CVSSP, and work under the direction of the Principal Investigator Prof Wenwu Wang, and in collaboration with the industrial partner.

CVSSP is an International Centre of Excellence for research in Audio-Visual Machine Perception and AI, with over 180 researchers. The Centre has state-of-the-art audio and video capture and analysis facilities supporting research in real-time video and audio processing and visualisation. CVSSP has a compute facility with 300 GPUs and >2PB of high-speed secure storage. The post-holder will also have access to the compute resources from Surrey Institute of People Centred AI, including 200+ state-of-the-art GPUs. 

How to apply

Please apply with your CV and cover letter on the University website. 

For informal inquiries, please contact Prof Wenwu Wang (Email: w.wang@surrey.ac.uk; Web: https://personalpages.surrey.ac.uk/w.wang/).

The University of Surrey reserves the right to close this vacancy early or extend based on Volume and Calibre of applications.

Further details

For more information and to apply online, please download the further details and click on the 'apply online' button above.
 
In return we offer a generous pension, relocation assistance where appropriate , flexible working options including job share and blended home/campus working locations (dependent on work duties), access to world-class leisure facilities on campus, a range of travel schemes and supportive family friendly benefits including an excellent on-site nursery.

Click here to find out more about the benefits we offer to support you.

The University of Surrey is committed to providing an inclusive environment that offers equal opportunities for all.  We place great value on diversity and are seeking to increase the diversity within our community.  Therefore we particularly encourage applications from under-represented groups, such as people from Black, Asian and minority ethnic groups and people with disabilities.

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