PhD Studentship: Beyond Pilots: De-Risking the Scale-Up of Artificial Intelligence in Digitally Enabled Circular Supply Chains

Overview

This PhD studentship investigates why artificial intelligence scaling fails in operational settings and how these failures can be anticipated and mitigated. The project focuses on digitally enabled circular supply chains, specifically examining food and perishable goods supply chains where forecasting and inventory decisions impact spoilage, waste, and carbon emissions. The research approaches scaling failure as a socio-technical systems problem involving governance workflows, validation gates, and operational pressure. The work is structured across three integrated phases, including a systematic review, a multi-case empirical study, and an agent-based simulation, culminating in a scaling-readiness framework.

Who can apply

Applicants from engineering, computer science, data science, operations management, information systems, and related disciplines are welcome to apply. Individuals with experience in data-driven or artificial intelligence-enabled operational environments, or those returning to academic study after industry, are particularly encouraged.

What you get

The studentship provides funding for tuition fees and an annual stipend of £21,805 per annum for the 2026/7 period. The successful candidate will join a supervisory environment covering sustainable operations, analytics, artificial intelligence, and computational modelling, with access to research facilities including the ECCE, INDEX, and the IDSAI. The position also includes an extended industry placement offering exposure to live operational challenges and knowledge exchange, along with training in computational simulation, mixed-methods research, artificial intelligence governance, and industry engagement.

Requirements

The research involves a systematic literature review, a multi-case empirical study utilizing interviews across strategic, operational, and frontline roles alongside deployment data analysis, and an agent-based simulation modeling control degradation under operational load. The resulting framework is validated through a survey of operations professionals.

How to apply

Applications should be submitted through the established institutional channels by the specified closing date.

Key dates

The closing date for applications is 2026-12-08.