Research Fellow in Deep Learning for Robot Audition

Are you keen to pioneer machine learning models that address the challenges of robot perception? 

We are recruiting a research fellow who will work on our EPSRC-funded research project on “Active Audition for Robots (ActivATOR)” under the direction of Dr Christine Evers. The position will be in the Vision, Learning and Control (VLC) Group, which is part of the School of Electronics and Computer Science in the University of Southampton. 

ActivATOR will develop novel machine learning models that enable robots to leverage the motion of their own bodies (‘egomotion’) to make sense of acoustic environments (e.g., shopping malls). Located at the intersection of machine learning, robotics, and acoustic signal processing, the project will bring together a highly interdisciplinary team of researchers, industry partners, and external academic collaborators.

The position is available on a fixed term basis (end date 8 October 2027) due to funding restrictions. As part of your role, you will:

• Develop novel model architectures for deep learning applied to audio data.
• Deploy your models onboard robotic systems.
• 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.
• Design and participate in engagement activities with the public, policymakers and key stakeholders to ensure societal benefit of your research.

The successful candidate will have a Ph.D. (either awarded or nearing completion) or equivalent work experience in deep learning, 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).

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 and robotic systems.
• 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.

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 (https://www.ecs.soton.ac.uk/workinghere). 

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

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