Research Fellow Edge Computing for AI

Full Time Fixed Term to 16/06/2027

Aplications are invited for two Research Fellow positions specialising in Edge Computing for AI at the National Edge AI Hub. The position is full-time for a duration until 16/06/2027 with potential for extension

You will be part of the EPSRC National Edge Artificial Intelligence Hub, a strategic investment by the UK Research and Innovation (UKRI) to advance fundamental research protecting data quality and AI algorithm learning when subjected to cyber attacks in Edge Computing environments.

At the Edge AI Hub, you will join an internationally renowned and multi-disciplinary team co-led at Southampton Dr. Jennifer Williams and Prof Sarvapali (Gopal) Ramchurn.

The role will involve a core focus on making complex speech and audio Edge AI models work efficiently on diverse edge computing systems. The successful candidate will carry out multidisciplinary research focused on AI systems for edge computing applications in speech processing. This includes:

• Developing advanced voice verification, recognition, and anti-spoofing systems optimized for edge devices
• Researching methods for audio quality estimation and enhancement in resource-constrained environments
• Creating innovative voice analysis techniques that can operate efficiently on edge computing platforms and resource-constrained environments
• Working on the entire lifecycle of AI voice products (from idea generation and training to implementation and governance)

Your research will directly contribute to making Edge AI more accessible to developers and enhancing its performance across various sectors including smart transport, health, energy, manufacturing, and smart cities.

To be successful you will have:

• PhD in Computer Science, Data Science, Machine Learning, Electrical Engineering, or a related field with focus on speech processing, edge computing, TinyML, distributed systems, or AI optimisation
• A strong publication record in relevant venues (ICASSP,  Interspeech, AAAI, EdgeSys, ICDCS, IEEE IoT Journal, IEEE Transactions on Mobile Computing, IEEE Transactions in Speech and Language Processing)
• Demonstrable experience with edge AI deployment, resource-constrained machine learning, and/or distributed computing and federated learning
• Experience or interest in interdisciplinary research crossing hardware, software, networking, and AI domains
• Excellent ability to present complex technical concepts clearly in both written form and orally

Applications for the position 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 PhD qualification being awarded the title of Senior Research Assistant will be given.

For further information about the Edge AI Hub and its research themes, please visit: https://edgeaihub.co.uk/

Further details:

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 on +44(0)2380 592750 or recruitment@soton.ac.uk quoting the job number.

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