Research Fellow in Machine Learning for Speech Processing

Research Fellow in Machine Learning for Speech Processing

Section: Institute of Sound & Vibration Research
Location: Highfield Campus
Salary: £35,880 to £39,105 Per Annum
Full Time Fixed Term to 31/01/2027
Closing Date: Friday 31 January 2025
Interview Date: To be confirmed
Reference: 2947724DA

We are seeking applications for a research fellow at the University of Southampton within the Institute of Sound and Vibration Research, to work in the area of machine learning for speech processing. The position is available on a fixed term basis until 31/01/2027.

You will be working on a Huawei-sponsored research project aimed at developing improved methods for processing speech in noisy and reverberant environments. You will work under the direction of the Principal Investigator, Prof Philip Nelson and in close collaboration with the project sponsors. The aim of the project is to investigate the use of state of the art machine learning methods for improving the quality of speech in teleconferencing systems. An important feature of the work is to identify methods that can be used within the constraints provided by commercially available computational resources for real-time processing. As part of your role, you will:

- Publish and disseminate your findings at top-tier venues (e.g., NeurIPS, ICLR, ICML, IEEE Transactions)
- Collaborate with our project sponsors to ensure the commercial impact of your research
- Develop and participate in activities for engagement with the public, policymakers and key stakeholders

You will benefit from:

- Extensive opportunities for collaboration with our project sponsors
- Access to state-of-the-art research facilities, including high-performance computing facilities and a suite of acoustical laboratories for undertaking experimental work
- A vibrant, diverse, and inclusive academic community
- Opportunities for professional development and career growth, e.g., mentorship of PhD students, development of funding applications, involvement in teaching activities
- Opportunities for career development, including contributions to teaching, generation of future funding bids, and co-supervision of PhD, taught postgraduate and undergraduate projects

We are seeking candidates with a Ph.D. (either awarded or nearing completion) or equivalent professional qualification and experience in machine learning, speech processing, or a related field, who have in-depth knowledge in, and demonstrable experience with:

- Recent developments in machine learning, particularly those used in the field of speech processing.
- The development and use of computational resources and associated specialist software for use in machine learning and speech processing.

Ranked in the top 1% of universities globally and among the UK's top 20 for research, the University of Southampton has an international reputation for its research, teaching and enterprise activities. The post will be held in the Institute of Sound and Vibration Research, a friendly and supportive environment that facilitates high-impact, multi-disciplinary research, education, training, and outreach.

We will give due consideration to applicants who wish to work flexibly including part-time, and to those who have taken a career break.

Informal enquiries can be made to Prof Philip Nelson.

Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title of Research Fellow will be applied upon successful completion of the PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given.

As a university, we aim to create an environment where everyone can thrive and are proactive in fostering a culture of inclusion, respect and equality of opportunity. We believe that we can only truly meet our objectives if we are reflective of society, so we are passionate about creating a working environment in which you are free to bring your whole self to work. With a generous holiday allowance as well as additional university closure days, we are committed to supporting our staff and students and open to a flexible working approach.

Apply by 11.59 pm GMT on the closing date. For assistance contact Recruitment, quoting the job number.