PhD Studentship: Digital Twins for waste reduction in Industry 5.0

Overview

This PhD studentship focuses on investigating the development of intelligent digital twin frameworks to predict, monitor, and reduce waste in manufacturing processes. The research explores the integration of near real-time data from industrial sensors, machinery, and production systems into digital twins to identify inefficiencies, detect anomalies, predict product defects, and optimise raw material usage. The project also examines simulation-based approaches that allow manufacturers to evaluate alternative production scenarios and assess their potential impact on waste generation prior to real-world implementation. The successful candidate will contribute to research addressing industrial waste and environmental sustainability in alignment with Industry 5.0, with opportunities to develop digital twin solutions, publish research in leading academic venues, and explore practical applications.

Who can apply

This studentship is available to UK applicants. The standard minimum entry requirement is a 2:1 bachelor's degree.

What you get

The funding for this project is provided through a competition for a Faculty of Science funded studentship. It covers home tuition fees and provides an annual stipend for three years. The current institutional PhD stipend rate is £21,805 per annum, which is subject to any agreed inflationary uplift for the 2027 to 2028 period.

Requirements

Applicants must hold the standard minimum entry requirement of a 2:1 bachelor's degree. The study mode for this position is full time and the work arrangement is on site.

Key dates

The closing date for applications is 2027-02-24. The expected start date for the project is 1 October 2027.