PhD Studentship: Skill Acquisition in Lifelong Robot Learning with Large Language Models
2 weeks ago
Supervisory Team: Dr. Muhammad Burhan Hafez (Lead Supervisor), Professor Adam Sobey
PhD Supervisor: Muhammad Burhan Hafez
Project description:
The integration of Large Language Models (LLMs) into robot learning has recently demonstrated remarkable success. It became possible to ground LLMs in the physical context and solve long-horizon robotic tasks efficiently by querying LLMs to generate a sequence of natural language commands corresponding to pretrained skills that accomplish a given task. LLMs have also enabled few-shot adaptation to novel tools by generating task-agnostic tool descriptions for language-conditioned learning of manipulation skills.
Long-horizon task learning and few-shot adaptation, supported by LLMs, are essential to lifelong robot learning. However, the current utilization of LLMs remains incompatible with the continual learning setting, wherein tasks are sequentially presented to the robot without a predefined task distribution. Moreover, the robot is expected to retain knowledge of previous tasks when learning new ones.
This project aims to explore how LLMs can be harnessed to continuously acquire new skills to solve novel tasks as opposed to mastering a predefined and fixed set of tasks. In particular, methods for incrementally learning skill representations jointly from textual descriptions and spatio-temporal information of action sequences will be developed and evaluated on learning visuomotor robotic tasks in a household environment.
You will join the School of Electronics and Computer Science which is ranked 1st in the UK for Electrical and Electronic Engineering (Guardian University Guide 2022) within the University of Southampton which is ranked in the top 1% of universities worldwide. The successful candidate must have a strong background in machine learning. Prior knowledge of reinforcement learning, robotics and training and finetuning LLMs is highly desirable.
Prospective candidates are invited to apply soon, as we will be reviewing applications on a rolling basis until the position is filled. PhD funding happens every one or two months, and once funded this position will close.
If you wish to discuss any details of the project informally, please contact Dr. Muhammad Burhan Hafez, Email: burhan.hafez@soton.ac.uk
Entry Requirements
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).
Closing date: 31 August 2024.
Applications will be considered in the order that they are received, the position will be considered filled when a suitable candidate has been identified.
Funding: We offer a range of funding opportunities for both UK and international students, including Bursaries and Scholarships.
For more information please visit PhD Scholarships | Doctoral College | University of Southampton
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
How To Apply
Apply online: Search for a Postgraduate Programme of Study (soton.ac.uk). Select programme type (Research), 2024/25, Faculty of Physical Sciences and Engineering, next page select “PhD Computer Science (Full time)”. In Section 2 of the application form you should insert the name of the supervisor: Muhammad Burhan Hafez
Applications should include:
- Research Proposal
- Curriculum Vitae
- Two reference letters
- Degree Transcripts/Certificates to date
We offer a range of funding opportunities for both UK and international students, including Bursaries and Scholarships
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