PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)

Large language models (LLMs) can read and write text and code, call tools, and follow instructions. They now allow us to build agents that plan and act over many steps instead of giving a single reply. LLM-based agents is becoming a key part of our everyday life and work, handling multi-step actions in a variety of application domains. However, an important open challenge is making these agents work well in real environments, achieving reliable results, correct use of tools, and predictable cost and speed across heterogeneous infrastructures and devices.

To address this challenge, we are recruiting PhD students to work on this exciting topic of LLM-based agentic AI, with the goal of making AI agents reliable, efficient, and collaborative. The research results are expected to become the core of next generation agentic AI systems. In this PhD programme, you will redefine how the world works, learns, and discovers, turning bold ideas into tools used by millions. You will then become one of the few early experts in practical agentic AI.

Potential Research Themes

• Foundations of LLM-based agents
• Broader LLM enablers for agents
• Multi-agent collaboration and coordination
• Agentic systems and distributed infrastructure
• Applications of agentic AI

What You Will Get

• An inclusive and open-minded research environment that bridges theoretical thinking and system building, with opportunities to publish and present at top AI/ML venues and validate ideas on real platforms.
• Mentorship focused on visionary brainstorming, in-depth technical discussions, and collaborative work culture on both theory and systems development.
• Opportunities to interact with other academic and industry partners working on advanced LLM systems.
• Access to computing resources for running LLM-based experiments.

Who You Will Work with

The lead supervisor Prof. Shiqiang Wang (https://shiqiang.wang) has recently moved to the University of Exeter after nearly 10 years of industry experience in the United States. He will bring a unique vision, hands-on expertise, and team spirit from his experience in both academic and industrial research. A supervisory team including at least one additional secondary supervisor will be established for each student. The prospective secondary supervisors Dr. George De Ath and Dr. Jawad Fayaz have significant experience in air traffic control and environmental intelligence, respectively, as well as in the general areas of machine learning, uncertainty quantification, and Bayesian modelling. They will provide complementary expertise to bridge agentic AI with real-world impact.

What We Are Looking from You

• Background in Computer Science or a related field.
• Strong motivation to conduct groundbreaking AI research that make a positive impact in the real-world.
• Excellent communication skills in English, both speaking and writing.
• Proficiency in programming and modern ML tooling (e.g., Python, PyTorch); experience with LLMs (e.g., using Hugging Face libraries) is a plus.
• Ability to reason about complex systems and turn ideas into code and running experiments.
• Curiosity, persistence, and team spirit.
• Good to have but not required: Applicants with prior industry experience (including internship) or experience with open-source contributions are particularly encouraged to apply.

The studentship covers international tuition fees plus stipend for living and will be awarded on the basis of merit. Both UK and international applicants are welcome.

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