[Jobs] Last Chance: Fully Funded PhD in Sustainable Robot Learning, Univ. Southampton, UK – Apply by 31 Aug!

[Burhan Hafez]

Dear colleagues,

We're hiring a PhD student to develop a sustainable, lifelong on-device robot learning system at the University of Southampton.

Project Title

Resource-efficient lifelong robot learning

About the PhD Project

Equipping robots with the ability to learn a growing set of tasks over their operational lifetime—rather than focusing on mastering individual tasks—presents a significant challenge in robot learning. Lifelong learning robots often struggle with catastrophic forgetting when learning from changing input distributions, which causes the robot to forget old knowledge when learning new tasks. They are also expected to leverage previous knowledge to accelerate learning of new tasks without the need for complete retraining. This is often referred to as the stability-plasticity dilemma, where stability denotes the retention of old knowledge, and plasticity refers to the acquisition of new knowledge.

Recent advancements in lifelong and continual learning have proposed three primary strategies to address this dilemma: regularization, dynamic growth, and experience replay. However, these methods typically demand high storage and computational resources, leading to increased energy consumption for data storage, processing, and transmission. Additionally, robots often face limitations in onboard resources, making it difficult to support lifelong learning outside controlled lab environments and to retain and integrate experiences from various environments and tasks. Although some recent approaches have shown promise in improving efficiency in continual robot learning, they often come at the cost of reduced performance compared to single-task models, where each task is learned with a dedicated model.

This project aims to develop a continual on-device robot learning system that improves the trade-off between stability and plasticity while enhancing resource efficiency without compromising performance. The system will be designed for deployment on resource-constrained, non-networked robotic platforms and aims to contribute to sustainability by reducing carbon emissions through improved operational efficiency, including minimizing the need for frequent retraining and optimizing data handling processes.

Funding Available For

UK, EU and Horizon Europe Associated Countries

Entry Requirements

1. A very good undergraduate degree (at least a UK 2:1 honours degree) or its international equivalent 
2. IELTS 6.5 (or equivalent) for non-native English speakers

How to Apply

Please send your pre-application package including CV, transcripts, sample publications (if any), two references and cover letter expressing your research vision and interest in the position to burhan...@soton.ac.uk

Closing Date

31 August 2025. Applications will be considered in the order that they are received. The position will be considered filled when a suitable candidate has been identified.

For more information, please visit: https://www.southampton.ac.uk/study/postgraduate-research/projects/resource-efficient-lifelong-robot-learning

Best regards, 

Muhammad Burhan Hafez

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Dr. Muhammad Burhan Hafez

Assistant Professor

School of Electronics & Computer Science

University of Southampton

Southampton SO17 1BJ, UK

E-mail: burhan...@soton.ac.uk

Homepage: https://www.soton.ac.uk/people/65b6st