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Research Fellow in Bayesian Machine Learning for Psychoacoustic Modelling

University of Southampton - School of Electronics and Computer Science (ECS)

Location: Southampton
Salary: £34,980 to £41,732
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 5th December 2023
Closes: 12th January 2024
Job Ref: 2534723FP
 

We are recruiting a postdoctoral research associate who will work on a large-scale research programme on “Challenges in Immersive Audio Technology (CIAT)” conducted in collaboration between King’s College London, University of Surrey, and University of Southampton.

Immersive technologies will transform our experience of the physical world, from museums to cars and classrooms. Despite significant progress in the computer vision community, long-standing fundamental challenges impact on audio technologies, preventing the immersion of an audience in an alternate reality. Existing technologies a) suffer from computational requirements preventing real-time creation of shared, interactive immersive audio experiences, and b) are limited in their ability to efficiently deliver shared, high-quality auditory experiences in 3D soundscapes to multiple listeners. CIAT’s vision is to transform the state of the art by developing a novel framework for capturing and reproducing only perceptually relevant information.

We are seeking applications for a research fellow, available on a fixed term basis for 36 months due to funding restrictions. As part of your role, you will:

  • Develop novel Bayesian machine learning approaches for psychoacoustic modelling.
  • Publish your findings at top-tier venues.
  • Disseminate your research findings at national and international workshops and conferences.
  • Collaborate with internal and external researchers to broaden the scope of your research.
  • Liaise with our industry partners to ensure commercial impact of your research.

You will benefit from:

  • Extensive opportunities for collaboration with external project partners.
  • Opportunities to travel, e.g., for international conferences and research visits hosted by project partners.
  • Access to state-of-the-art research facilities, including dedicated laboratory space.
  • 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.

We are seeking candidates with:

  • A Ph.D. (either awarded or nearing completion) or equivalent professional qualification and experience in Computer Science, Engineering or a related field.
  • Demonstratable experience in one of the following areas, evidenced by publications in top-tier conferences or journals: Bayesian inference, deep learning, or psychoacoustic modelling.
  • Excellent programming skills (e.g., TensorFlow, PyTorch).
  • Proficiency in data analytics, pre-processing, and feature engineering.

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 School of Electronics and Computer Science (ECS), a friendly and supportive environment that facilitates high-impact, multi-disciplinary research, education, training, and outreach. ECS holds an Athena SWAN bronze award in recognition of its continued commitment to improving equality for women in science and engineering. 

We will give due consideration to applicants who wish to work flexibly including part-time, and to those who have taken a career break. We have a range of staff development programmes and a unique mentoring and wellbeing scheme (https://www.ecs.soton.ac.uk/workinghere).

Applications 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 completion of PhD.   Prior to the qualification being awarded the title of Senior Research Assistant will be given.

Informal enquiries can be made to Dr Christine Evers, Associate Professor: c.evers@soton.ac.uk

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