Audio/acoustics Machine Learning

University of Surrey

One fully-funded PhD studentship including fees and stipend is available for an outstanding candidate to join the Centre for Vision, Speech and Signal Processing (CVSSP), part of the University of Surrey’s Institute for People-centred Artificial Intelligence (PAI), in partnership with Fraunhofer Institute for Integrated Circuits IIS.

Here is an exciting opportunity for a budding researcher to fulfil their potential at the intersection of Artificial Intelligence (AI) and Audio/acoustics, an area of machine learning called Machine Listening. The PhD project brings together world-leading audio experts to develop state-of-the-art techniques as a widely-applicable embedding of acoustic environments.

 The project forms a collaboration between CVSSP at the University of Surrey (Guildford, UK) and Fraunhofer IIS (Erlangen, Germany). It builds on work by the co-investigators into virtual acoustics, spatial audio rendering, optimisation of acoustical systems, training of deep neural networks and exploration of object-based audio for making translatable immersive experiences. As such, the research is expected to include a mixture of practical and computational experiments, based at the university. The successful candidate will have the chance to spend time in the labs at Fraunhofer, interacting with colleagues there and exchanging knowledge.

Supervisors: Prof Philip Jackson

Entry requirements

Open to any UK or international candidates. Up to 30% of our UKRI funded studentships can be awarded to candidates paying international rate fees. Find out more about eligibility. Starting in January 2024. Later start dates may be possible – please contact Prof Philip Jackson once deadline passes.

You will need to meet the minimum entry requirements for our PhD programme.

You will have a strong interest in audio and machine learning, and demonstrate a high level of academic achievement in relevant subject areas and a clear aptitude for scientific, engineering research. We will need to be convinced that you have the necessary background knowledge and research skills to begin your doctoral training. You will have a 1st or 2:1 BSc/BEng degree (or equivalent) and either an MSc/MEng in a relevant engineering or scientific discipline or equivalent specialist experience. You will be able to demonstrate excellent mathematical, analytical and computer programming skills. Advantage will be given to applicants with experience in one or more of the following: machine listening, deep learning, acoustics, signal processing, computer vision, spatial audio, NLP, statistical analysis, software development, academic writing. You will have advanced research skills, evidenced by a significant Bachelors/Masters project, for example, involving experimental research, appropriate use of the literature, computer-based simulations and a formal dissertation-style report.

How to apply

If you’re interested in submitting an application, please email Professor Philip Jackson in the first instance by emailing  to find out how to apply.

To help us track our recruitment effort, please indicate in your email – cover/motivation letter where ( you saw this posting.

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