Research Fellow in Bayesian Machine Learning

Job title:

Research Fellow in Bayesian Machine Learning

Company

Job description

Offer DescriptionYou will join our team working on deep learning for machine listening to work on uncertainty quantification for deep auditory models. The position will be in the Vision, Learning and Control (VLC) Group, which is part of the in the University of Southampton. You will work under the direction of Dr Christine Evers on the EPSRC research programme “Challenges in Immersive Audio Technology (CIAT)” ( ), which is conducted in collaboration with the Institute of Sound and Vibration Research (ISVR), King’s College London and the University of Surrey.The vision of CIAT is to deliver real-time, immersive audio experiences to audiences involving multiple listeners by capturing and reproducing only perceptually relevant information. As part of this position, you will develop novel methods based on deep learning that enable the prediction of perceptual attributes associated with uncertainty (e.g., the source location). The outputs of your research will be used within the CIAT consortium for the generation of high-quality immersive audio experiences.The successful candidate will have a Ph.D. (either awarded or nearing completion) or equivalent work experience in deep learning or audio signal processing, as well as:

• Demonstrable experience with the development of novel model architectures for deep learning applied to audio data;
• In-depth knowledge of deep learning, including recent developments;
• Significant experience with the development of custom modules using GPU-accelerated APIs for deep learning (e.g., Pytorch); and
• Publications in top-tier venues in Machine Learning and/or Signal Processing (e.g., NeurIPS, ICML, IEEE Transactions in Audio, Speech and Language Processing).

The position is available on a fixed term basis for 36 months due to funding restrictions. As part of your role, you will:

• Publish and disseminate your findings at top-tier venues;
• Collaborate closely with our external partners, e.g., Stanford CCRMA (USA);
• Liaise with our industry partners to ensure commercial impact of your research; and
• Develop and participate in activities for engagement with the public and key stakeholders.

You will benefit from:

• Extensive opportunities for collaboration and travel, e.g., for international conferences and research visits hosted by project partners.
• Access to state-of-the-art research facilities, including a high-performance compute cluster that is specifically aimed at training deep learning models.
• A vibrant, diverse, and inclusive academic community, e.g., coffee mornings, journal clubs, group away days.
• Opportunities for professional development and career growth, e.g., mentorship of PhD students, development of funding applications, involvement in teaching activities.

The department of Electronics and Computer Science is the leading university department of its kind in the UK, with an international reputation for world-leading research across computer science, electronics, and electrical engineering. Research takes place in a multidisciplinary, collaborative environment and draws on our outstanding facilities. With over 550 researchers from many different subject backgrounds, the research culture in ECS is fast-changing and dynamic. Our internationally renowned teaching and research have been ranked among the highest in the UK. 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 ( ).Informal enquiries can be made to Dr Christine Evers, Associate Professor: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.Where to apply WebsiteRequirementsAdditional InformationWork Location(s)Number of offers available 1 Company/Institute UNIVERSITY OF SOUTHAMPTON Country United Kingdom City Southampton GeofieldContact CitySouthamptonSTATUS: EXPIREDShare this page

Expected salary

Location

Southampton

Job date

Sun, 25 Aug 2024 22:14:11 GMT

To help us track our recruitment effort, please indicate in your email/cover letter where (globalvacancies.org) you saw this job posting.