Fully Funded PhD Studentship

The job requirements are detailed below.

Job details Job title Fully Funded PhD Studentship Job reference BEDS2957 Date posted 16/07/2026 Application closing date 16/08/2026 Location Luton Salary See below Contract Three year studentship Contractual hours 35 Basis Full time Job category/type Research Attachments Blank Job information

Fully Funded PhD Studentship in Responsible AI for Interview Assessment and Candidate-Organisation Compatibility (UK Home Applicants Only) Project: Three-Channel Interview Assessment: Responsible Multimodal AI for Fair and Evidence-Based Hiring Commercially Funded Doctoral Studentship in Collaboration with IMS Group , the University of Bedfordshire , and Luton AI .

A full time, fully funded PhD studentship for UK Home students 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.

The successful candidate will also become part of Luton AI, the University of Bedfordshire's applied AI ecosystem. Luton AI brings together academic research, specialist facilities, external partners and real world projects to support the responsible development and practical application of artificial intelligence.

Through the IMS Group funded studentship, the successful candidate will receive full tuition fee support, an annual stipend, academic supervision, access to research infrastructure and specialist facilities, doctoral training, and opportunities to engage with an international commercial partner.

Funding The studentship will provide:

• Full Home University tuition fees for three years - please note, this opportunity is only available to UK Home students.
• An annual stipend for up to three years - confirmed amount to be inserted.
• Access to specialist research facilities, computing infrastructure and doctoral training.
• Academic supervision and support from the University's research community.

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.

Key dates Closing date: Sunday 16 August 2026

Interview date: Virtual interviews will take place during the week commencing Monday 31 August 2026

Expected start date: October 2026

Study mode: Full time

Duration: Three years, subject to satisfactory progression

The project Interviews remain one of the most widely used methods of personnel selection, yet decisions can be influenced by inconsistent judgement, unstructured questioning and the way interviewers interpret verbal and non verbal behaviour. As recruitment becomes increasingly digital and AI assisted, there is a pressing need for methods that are demonstrably valid, fair, transparent and acceptable to candidates.

This PhD project will develop and empirically test a Three Channel Interview Assessment Model combining: verifiable attributes such as qualifications, work samples and assessed skills; self reported information such as experience, motivations and structured interview responses; and observable interaction signals such as gaze direction, facial movement, posture, gesture and vocal prosody.

The successful candidate will investigate how human interviewers combine these channels, the implicit weight assigned to each source of evidence, and how effects such as halo, similarity bias and cultural interpretation may influence decisions. Controlled experiments and policy capturing methods may be used to compare interviewer judgements with evidence based outcome measures.

The project will also explore machine learning, multimodal data analysis, computer vision, audio analysis and explainable AI methods. Rather than assuming that behavioural signals reveal personality, deception or suitability, the research will test whether any signals provide reliable and incremental information, under what conditions, and with what limitations.

Human, structured and AI assisted assessment approaches will be compared using appropriate measures of predictive validity, reliability and calibration. Where feasible, the research may include longitudinal validation against outcomes such as performance, progression, retention and candidate experience.

Fairness, privacy, informed consent, accessibility and human oversight will be central to the research design. Protected characteristics will not be used to determine candidate suitability; where demographic information is collected for approved research purposes, it will be used to identify and mitigate differential performance, bias or exclusion.

The longer term objective is to produce an evidence based and auditable framework for responsible interview assessment that supports better workforce decisions without replacing professional judgement or reproducing historical inequalities. The research will consider routes to practical evaluation within recruitment and workforce environments relevant to IMS Group.

Research environment The successful candidate will undertake the project within the University of Bedfordshire's growing artificial intelligence research and innovation environment and will be connected to the work of Luton AI.

Through Luton AI, the candidate will benefit from access to applied AI expertise, advanced computing infrastructure, specialist facilities and a wider network of academic and industry collaborators. The partnership with IMS Group will provide commercial context, sector insight and opportunities for knowledge exchange within recruitment and workforce solutions.

This environment will support the candidate in moving beyond the development of an AI model to consider research validity, human factors, explainability, governance, candidate experience and the practical translation of research into responsible recruitment practice.

Engagement with IMS Group: The successful candidate will be expected to engage proactively and professionally with IMS Group throughout the PhD, ensuring that the research remains academically rigorous while addressing relevant workforce and recruitment challenges.

This will include:

• Providing appropriate updates on research progress, emerging findings and professional development.
• Participating in relevant IMS Group meetings, workshops and knowledge exchange activities.
• Sharing appropriate research insights and outcomes with IMS Group, subject to ethical approval, confidentiality and data governance requirements.
• Acting as a positive ambassador for the University of Bedfordshire, Luton AI and the IMS Group research partnership.
• Contributing, where appropriate, to the translation of research into responsible recruitment and workforce assessment practice.

The candidate should be willing to develop a positive and constructive relationship with IMS Group and work effectively across academic and commercial environments.

Research objectives The successful candidate will:

• 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.

Person specification 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.

Applicants with relevant professional or technical experience in recruitment, assessment, HR technology, data analysis or AI who can demonstrate their ability to undertake doctoral level research may also be considered.

Knowledge Applicants should demonstrate knowledge of one or more of the following areas:

• 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.

Knowledge of recruitment practice, structured interviews . click apply for full job details