PhD Studentship: Explainable AI, Affordability, and Prescriptive Analytics for Sustainable Intelligent Maintenance

About the Project

REFERENCE NUMBER

Please select SCEBE/23Stu/McGlinchey

BACKGROUND AND AIMS

Building on work already completed or currently underway at the Digital Transformation and Intelligent Maintenance (DTIM) Research Group and in collaboration with the school's research centres in Smart Technology, Built Environment Asset Management and Climate Justice, this interdisciplinary theme aims at investigating and developing solutions for a societal challenge using digital technologies. Moreover, our research group has external industry and academic links with key players in this field.

As part of Industry 4.0, maintenance activities are being optimised digitally with data-driven methods built on artificial intelligence (AI). Three significant components that make up the overall goal of this research are:

• Affordability: Digital Solutions for Small and Medium-Sized Enterprises (SMEs)

• Explainable Artificial Intelligence: Design of a Trustworthy Digital Maintenance Framework

• Prescriptive Analytics: Design of Prescriptive Maintenance Framework

Candidates must include an outline of their ideas for exploring digital solutions for small and medium enterprises. Also, in Industry 4.0 for solving the societal challenge in build resilient infrastructure, promote sustainable industrialization and foster innovation.

The successful candidate is advised to look at current projects: (https://www.gcu.ac.uk/cebe/research/smarttechnologycentre/projects/) to identify which areas are of interest to the SMART Technology Centre and develop a proposal.

The successful candidate will have an Engineering (Industrial, Mechanical, Power, Electronics, Telecommunications etc.)/ Computer Science or Computing) and/or data science background (First Class or 2:1 Honours) and a Master’s degree (ideally at least Merit) in a related area or at the interface between the two (e.g. AI, machine learning or Engineering, Computer Science). They will have experience of maintenance or willing to learn it as well as experience and knowledge of some quantitative research methods. Prior work in Industry 4 or predictive analytics and digital twins, is desirable.

Please send any informal queries about the project to:

Name: Prof Don McGlinchey

Email: d.mcglinchey@gcu.ac.uk

GCU Research Online URL: https://researchonline.gcu.ac.uk/en/persons/don-mcglinchey

This project is available as a 3 years full-time PhD study programme with expected start date of 1 October 2023. Candidates are encouraged to contact the research supervisors for the project before applying.

Please note that emails to the supervisory team or enquires submitted via this project advert do not constitute formal applications; applicants should apply using the Application Process page, choosing October 2023 Start. Applicants shortlisted for the PhD project will be contacted for an interview within six weeks from the closing date. 

Please send general enquires regarding your application to: researchapplications@gcu.ac.uk 

Funding Notes

The GCU studentship is worth at least £22,548 per year for three years. The studentship covers payment of tuition fees (£4,880 for Home/RUK students or £16,800 for EU/International students) plus an annual stipend of £17,668 for Home/RUK students or an annual scholarship of £6,548 for EU/International students.

EU/International candidates of outstanding calibre may be awarded a studentship of £34,468 per year for three years. The International Enhanced Scholarship covers payment of tuition fees (£16,800) plus an annual stipend of £17,668.

For further details please see our Fees and Funding and Research Scholarships and Studentships webpages.

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