Fully Funded PhD Studentship in Three-Channel Interview Assessment: Responsible Multimodal AI for Fair and Evidence-Based Hiring

About the role

A fully funded PhD studentship is available at the University of Bedfordshire to develop and evaluate responsible artificial intelligence methods for interview assessment and candidate-organisation compatibility. The studentship is commercially sponsored by IMS Group and will connect doctoral research with a major international workforce-solutions business operating across recruitment, finance, data, marketing and managed IT services.

Responsibilities

• Develop and refine a Three-Channel Interview Assessment Model combining verifiable, self-reported and observable interaction data.
• Investigate how interviewers weight different sources of evidence and how cognitive, social and cultural biases affect judgement.
• Design ethically approved protocols for collecting and analysing interview, audio, video and assessment data.
• Develop interpretable multimodal AI methods and test whether they provide reliable incremental value beyond structured assessment.
• Compare human, structured and AI-assisted decisions against appropriate measures of performance, progression, retention and candidate experience.
• Evaluate fairness, privacy, accessibility, neurodiversity, informed consent and human-oversight requirements.
• Publish research findings in relevant peer-reviewed journals and conferences.
• Communicate research progress and outcomes to academic, professional and non-specialist audiences.

Requirements

The successful candidate should have:

• A good honours degree, normally at least a UK 2:1 or international equivalent, in computer science, artificial intelligence, data science, human-computer interaction, psychology, organisational psychology, business analytics or a closely related subject.
• A relevant master's degree, or equivalent research or professional experience, would be advantageous.
• Knowledge of artificial intelligence and machine learning, human-computer interaction, behavioural research or experimental design, computer vision, audio analysis or multimodal data analysis, statistics, psychometrics or quantitative research methods, personnel selection, organisational psychology or person-environment fit, explainable, responsible or human-centred AI, research ethics, fairness, privacy or governance in data-driven systems.
• Experience in programming in Python, R or a comparable language, using machine-learning frameworks such as PyTorch, TensorFlow or scikit-learn, working with audio, video, behavioural, assessment or longitudinal data, designing experiments, surveys or quantitative evaluation studies, applying statistical modelling, psychometrics or machine-learning evaluation methods, working in interdisciplinary research or with external organisations, preparing academic reports, technical documentation or research publications.

Qualifications

Applicants should normally have:

• A good honours degree, normally at least a UK 2:1 or international equivalent, in computer science, artificial intelligence, data science, human-computer interaction, psychology, organisational psychology, business analytics or a closely related subject.
• A relevant master's degree, or equivalent research or professional experience, would be advantageous.

Skills and competencies

• A logical, analytical and methodical approach to problem-solving.
• The ability to plan and undertake research independently.
• Strong written and verbal communication skills.
• The ability to explain complex technical and behavioural concepts clearly to specialist and non-specialist audiences.
• Careful research-data management and record-keeping.
• The ability to work effectively with academic, technical, professional and industry collaborators.
• A strong understanding of ethical and responsible research involving AI, people and potentially sensitive data.
• High levels of motivation, initiative and intellectual curiosity.
• The ability to manage competing priorities and work to agreed deadlines.
• A willingness to learn new technical, statistical and research methods.
• A willingness to engage proactively and professionally with IMS Group.

Benefits

The studentship provides:

• Full Home University tuition fees for three years.
• An annual stipend for up to three years.
• Access to specialist research facilities, computing infrastructure and doctoral training.
• Academic supervision and support from the University's research community.

Pay

The stipend will be awarded annually for up to three years, subject to satisfactory academic progression and in accordance with the funding agreement between IMS Group and the University of Bedfordshire.

Schedule

The expected start date is October 2026, with the project duration being three years, subject to satisfactory progression.