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Shiqiang Wang

1 week ago

Fully Funded PhD in LLM-Based Agentic AI at University of Exeter University of Exeter in United Kingdom

I am recruiting fully funded PhD students in LLM-based Agentic AI at the University of Exeter.

University of Exeter

United Kingdom

email-of-the@publisher.com

Nov 30, 2025

Keywords

Computer Science
Information Technology
Artificial Intelligence
Distributed System
Multi-agent System
Large Language Models

Description

The University of Exeter's Department of Computer Science is offering a fully funded PhD studentship in the field of LLM-Based Agentic AI: Foundations, Systems & Applications. This opportunity focuses on the development and improvement of large language model (LLM)-based agents, aiming to make them more reliable, efficient, and collaborative in real-world environments. Research themes include the foundations of LLM-based agents, multi-agent collaboration, distributed infrastructure, and practical applications of agentic AI. The lead supervisor is Professor Shiqiang Wang, with additional supervision from Dr. George De Ath and Dr. Jawad Fayaz. Applicants should have a strong background in computer science or a related field, proficiency in programming and modern machine learning tools, and excellent communication skills. Experience with LLMs and prior industry or open-source contributions are advantageous. The studentship covers international tuition fees and provides a generous annual stipend. Both UK and international students are encouraged to apply. The application deadline is November 30, 2025. For more information, visit the supervisor's academic page or the university's website.

Funding

The studentship covers UK and international tuition fees and provides an annual tax-free stipend of at least £20,780 per year. Funding is awarded based on merit and is available to both UK and international applicants.

How to apply

Apply online through the University of Exeter's application portal before the deadline. Prepare your CV, cover letter, and supporting documents. Contact the lead supervisor if you have specific research questions. Ensure all materials are submitted by November 30, 2025.

Requirements

Applicants should have a background in Computer Science or a related field, strong motivation for ground-breaking AI research, excellent English communication skills, proficiency in programming and modern ML tools (such as Python and PyTorch), and ideally experience with LLMs (e.g., Hugging Face libraries). Ability to reason about complex systems, turn ideas into code, and run experiments is required. Curiosity, persistence, and team spirit are valued. Prior industry experience or open-source contributions are encouraged but not required.

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