Fully Funded Studentship: Human-Aligned Super-Resolution for Facial Identification: Behavioural[...]

University of Birmingham; United Kingdom; On-site; GBP 100,000 - 125,000; Full time

Job summary

A leading UK university is offering a PhD position focusing on the impact of generative AI in facial identification. The role involves conducting interdisciplinary research combining psychology and computer science. Candidates should have a strong academic record in relevant fields and are encouraged to apply, especially if they have coding or machine learning experience. This role provides the unique opportunity to work with industry leaders and gain hands-on experience in AI development.

Qualifications

• Candidates should have a strong academic background in relevant fields.
• Experience in coding and behavioural experimentation is desirable.
• Strong interest in human perception, AI ethics, and forensic science is encouraged.

Responsibilities

• Investigate how generative AI-based super-resolution technologies influence facial identification.
• Conduct behavioural experiments and apply machine learning techniques.
• Collaborate with industry partners on AI development projects.

Skills

Coding (Python/R/Matlab)

Behavioural experimentation

Statistics

Machine learning

Education

1st class or 2:1 undergraduate degree in Psychology, Cognitive Science, Computer Science, Neuroscience, Data Science, or a related field

MSc degree in a relevant area (desirable)

Job description

Psychological sciences » Cognitive science

Computer science

Organisation/Company University of Birmingham Department School of Psychology Research Field Psychological sciences » Cognitive science Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 17 Feb 2026 - 17:00 (Europe/London) Country United Kingdom Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Background

CCTV footage is a predominant and crucial source of evidence in policing, with an estimated 21 million cameras operating in the UK. Yet more than 80% of real-world footage is too poor in quality to support reliable person identification. This severely limits investigative success and leaves offenders unidentified.

Generative AI–based super-resolution (SR) technologies—such as VisionMetric’s iREVEAL—promise transformative gains by enhancing low-quality facial images. However, there is little scientific evidence on whether these tools improve human accuracy, how they affect machine recognition, and whether they introduce demographic biases.

This interdisciplinary PhD (Psychology w. Computer Science) will investigate how generative AI–based super-resolution (SR) technologies influence human and machine-based facial identification. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions:

• How do SR-enhanced images affect machine-based facial recognition, and where do human and machine decisions diverge?
• Do SR methods perform equitably across demographic groups?
• Can SR models be improved using human perceptual insights?

This project provides extensive interdisciplinary training from subject experts and industry, including in behavioural experimental design and statistical modelling; computer vision and AI techniques; explainable AI and human–machine comparison methods; and responsible innovation.

The student will work closely with VisionMetric , which is a leading SME supplying facial software to police forces in over 30 countries. Two placements at VisionMetric will provide hands-on experience with AI development pipelines and product development.

This is an exceptional opportunity to build a skillset spanning psychology, AI, fairness, and forensic technology, positioning the candidate for careers in academia, applied behavioural science, AI research, technology, or policy.

The project addresses both the societal risks and potential benefits of AI in high-stakes environments.

Candidate

We are looking for a highly talented and dedicated student with a 1st class or 2:1 undergraduate degree in Psychology, Cognitive Science, Computer Science, Neuroscience, Data Science, or a related field. An MSc degree in a relevant area is desirable though not necessary. Experience incoding (e.g.,Python/R/Matlab) and experience in behavioural experimentation, statistics, ormachine learning is desirable but full training will be provided. Applicants with an interest in human perception, AI ethics, or forensic science are especially encouraged.

Interviews for this studentship are expected to take place on 16thMarch 2026.