Publisher
source

Shiqiang Wang

6 months ago

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

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

December 31, 2026
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Country

United Kingdom

University

University of Exeter

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Keywords

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

About this position

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 details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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