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

University of Surrey - Innovative Media Technology

Qualification Type:	PhD
Location:	Guildford
Funding for:	UK Students, EU Students, International Students
Funding amount:	Fully and directly funded for this project only. Home or International fees for 42 months. UKRI standard stipend £21,805 pa (42 months) - for academic year 2026/27 RTSG: £1,500 pa. Additional conference funding (up to £3,000) may be available
Hours:	Full Time

Placed On:	27th March 2026
Closes:	30th May 2026
Reference:	PGR-2526-075

Video games are complex, continuously updated, and difficult to validate at scale. Manual QA struggles to cover vast interactive state spaces, and automated approaches often detect anomalies without explaining issues clearly or prioritising them by player impact. This collaborative doctorate (University of Surrey, SAHCI, and Sony Interactive Entertainment, SIE) will develop a QoE-driven agentic AI framework for automated bug discovery, reproducibility, and severity ranking in video games.

The research will implement a multi-agent workflow with three complementary roles: an Explorer agent that actively probes the game to discover failures; an Inspector agent that verifies and reproduces candidate issues, capturing minimal but sufficient evidence (inputs, states, clips, logs); and a Reporter agent that produces structured bug reports suitable for triage. A key novelty is an explicit QoE severity model that learns to rank bugs based on predicted player impact (for example frustration, immersion disruption, fairness issues, comfort or usability), using lightweight human feedback and QA expertise.

The project will evaluate improvements over scripted and random baselines using metrics such as confirmed unique bugs per hour, reproducibility rate, evidence quality, and correlation between severity ranking and human judgements. The student will work with SIE co-supervision and industry-informed glitch taxonomies and reporting requirements, under appropriate data, IP, and publication governance. The work also aligns with Surrey’s GAIN programme and games provision within SAHCI, and will support standards-oriented impact through the supervisory team’s engagement with ITU-T work on gaming QoE.

Supervisors: Dr Femi Adeyemi-Ejeye, Prof Wenwu Wang, Dr Nabajeet Barman and Dr Saman Zadtootaghaj

Entry requirements

Open to any UK or international candidates. Starting in October 2026.

You will need to meet the minimum entry requirements for our PhD programme.

We welcome applicants from Computer Science, Games Technology, Digital Media, or related disciplines. You should have some of the following:

• Strong programming skills (preferably in Python), with experience in machine learning/AI or software engineering for interactive systems
• Desirable experience in game development or design using platforms such as Unity, Unreal, or Godot
• Up-to-date knowledge of recent advances in generative AI, including vision-language models (VLMs) and agent-based AI systems
• Ability to design and conduct experiments involving human-centred evaluation, including quality of experience (QoE), usability, and preference studies

Excellent communication skills and the ability to collaborate effectively with industry partners, including working under confidentiality constraints.

How to apply

Once you discussed your project with a prospective supervisor you will need to make an application.

Applications should be submitted via the Innovative Media Technology PhD programme page.

In place of a research proposal, you should upload a document stating the title of the project that you wish to apply for and the name of the relevant supervisor.

Funding

Fully and directly funded for this project only.

Home or International fees for 42 months.

UKRI standard stipend £21,805 pa (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.

Application deadline: 30 May 2026

Enquiries: Contact Dr Femi Adeyemi-Ejeye

Ref: PGR-2526-075