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PhD Studentship: Human-centred Manufacturing Engineering with eXplainable AI (HUMANE-XAI)

Loughborough University

Qualification Type: PhD
Location: Loughborough
Funding for: UK Students
Funding amount: £25,000
Hours: Full Time
Placed On: 6th January 2026
Closes: 3rd March 2026
Reference: FP-MG-MTC/26

This project is an exciting opportunity to undertake industrially linked research in partnership with the Manufacturing Technology Centre (MTC). This PhD opportunity is based within Loughborough University’s Wolfson School of Mechanical, Electrical and Manufacturing Engineering, which conducts cutting-edge research into advanced manufacturing, applied AI and human factors.

Motivation
We are looking for a motivated PhD student to advance explainable AI (XAI) in manufacturing. As the manufacturing industry moves toward digitalisation and autonomy, trust and interpretability remain key barriers. Current XAI methods are often generic and overlook industrial realities. This project will embed user-centric explanations directly into machine learning workflows using structured, ontology-driven approaches validated by industry partners – ensuring AI systems are accurate, transparent, and aligned with stakeholder needs. Your research will help shape next-generation AI tools that enable trustworthy, human-centred decision-making in manufacturing. 

Aim
Working closely with MTC and industrial partners, you will design and validate a user-centred explainability framework that connects technical layers with human decision-making. Your work will deliver tools to assess explainability requirements, select appropriate XAI techniques (e.g., SHAP, LIME, counterfactuals), and develop novel explanation interfaces for industrial applications. As a PhD student, you will work with both academics from the Wolfson School, Intelligent Automation Centre and also have the opportunity to work with the engineering teams within the MTC. This will give you real-world experience in working within an industrial company, as well as experiencing the workplace and culture within it.

The MTC is an independent Research and Technology Organisation (RTO) focused on accelerating disruptive technologies in UK manufacturing. Supported by the government, it partners with industry and research bodies to drive innovation across all UK manufacturing sectors, from SMEs to large global manufacturers. For details, visit the MTC website.

Entry requirements:
A 1st or high 2:1 degree in computer science, manufacturing/industrial engineering, data science, human-computer interaction, or a closely related discipline. Experience in machine learning, data visualisation, or software engineering is highly desirable. An interest in sociotechnical systems or user-centred design methods would be beneficial.

English language requirements:
Applicants must meet the minimum English language requirements.

Funding information:
This fully funded 3-year studentship is available only to UK nationals. The successful applicant will receive a generous tax-free annual stipend of £25,000, full-time home tuition fees paid, and £2,000 per year for consumables and travel. Funding from MTC requires passing their security checks before starting the PhD.

Funding for this studentship is awarded on a competitive basis and is not guaranteed; availability will depend on the outcome of the selection process and subject to final approval by the University.

How to Apply:
All applications should be made online. Under Campus, please select ‘Loughborough’ and select Programme ‘Mechanical and Manufacturing Engineering’. Please quote the advertised reference number *FP-MG-MTC/26* in your application under the ‘Finance’ section. 

Applications must include a personal statement, up-to-date curriculum vitae (CV), details of two referees (one from your highest degree qualification), certified certificates and transcripts for all completed degree programmes, and a reference to the project ‘FP-MG-MTC/26’. 

Shortlisted candidates will be contacted for an online interview, which are expected in February/March 2026.

 

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