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Femi Adeyemi-Ejeye

6 months ago

PhD Studentship: QoE-Driven Agentic AI for Automated Bug Discovery in Video Games (Collaborative Doctorate with Sony Interactive Entertainment) University of Surrey in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

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Country

United Kingdom

University

University of Surrey

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Keywords

Computer Science
Machine Learning
Information Technology
Media Studies
Software Engineering
Digital Media
Video Game
Multi-agent System

About this position

[Fully and directly funded for this project only. Home or International fees for 42 months. UKRI standard stipend £21,805 per annum (42 months) for academic year 2026/27. RTSG: £1,500 per year. Additional conference funding (up to £3,000) may be available, subject to approval.]

This PhD studentship at the University of Surrey, in collaboration with Sony Interactive Entertainment, offers a unique opportunity to advance the field of automated bug discovery in video games using agentic AI. The project aims to develop a Quality of Experience (QoE)-driven multi-agent framework that automates bug discovery, reproducibility, and severity ranking in complex, interactive game environments. The research will focus on three agent roles: Explorer (actively probing games for failures), Inspector (verifying and reproducing issues with minimal evidence), and Reporter (generating structured bug reports for triage). A key innovation is the explicit QoE severity model, which ranks bugs based on predicted player impact, leveraging human feedback and QA expertise.

Evaluation will be conducted against scripted and random baselines, using metrics such as unique bugs per hour, reproducibility rate, evidence quality, and correlation between severity ranking and human judgements. The student will benefit from industry-informed glitch taxonomies, reporting requirements, and co-supervision from SIE, ensuring relevance to real-world game development and QA practices. The project aligns with Surrey’s GAIN programme and SAHCI’s games provision, supporting standards-oriented impact through engagement with ITU-T gaming QoE initiatives.

Funding is fully and directly provided for this project, covering home or international fees for 42 months, a UKRI standard stipend (£21,805 per annum), RTSG (£1,500 per year), and potential conference funding (up to £3,000). The studentship is open to UK and international candidates, starting in October 2026. Applicants should have strong programming skills (preferably Python), experience in machine learning/AI or software engineering for interactive systems, and ideally game development experience with platforms like Unity, Unreal, or Godot. Knowledge of generative AI, vision-language models, and agent-based AI systems is desirable, along with the ability to design and conduct human-centred evaluation studies.

Applications should be submitted via the Innovative Media Technology PhD programme page. Instead of a research proposal, upload a document stating the project title and supervisor name. For enquiries, contact Dr Femi Adeyemi-Ejeye or Prof Wenwu Wang. The application deadline is 30 May 2026.

Funding details

Available

What's required

Open to UK or international candidates. Applicants must meet the minimum entry requirements for the University of Surrey PhD programme. Preferred backgrounds include Computer Science, Games Technology, Digital Media, or related disciplines. Strong programming skills (preferably Python) and experience in machine learning/AI or software engineering for interactive systems are required. Desirable experience in game development or design using platforms such as Unity, Unreal, or Godot. Up-to-date knowledge of generative AI, vision-language models, and agent-based AI systems is advantageous. Ability to design and conduct human-centred evaluation experiments, including QoE, usability, and preference studies. Excellent communication skills and ability to collaborate with industry partners under confidentiality constraints.

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Professors

Professor of Signal Processing and Machine Learning

University Name
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United Kingdom

Research Interests

Phonetics

Music

Auditory Perception

Spatial Audio

Speech Recognition