close partnership with Samworth Brothers, one of the UK’s leading food producers, the research will apply advanced data analytics and artificial intelligence to identify vulnerabilities and emerging risks across critical ingredient and supplier networks, with the aim of delivering near real‑time, decision ready insight.

The project offers an exceptional opportunity for a PhD student to work on a high impact, real world industrial challenge while developing cutting edge skills in AI, data analytics and risk modelling. The student will work with complex industrial datasets, collaborate directly with supply chain and technical specialists, and produce research with clear academic and commercial relevance.

The studentship is suitable for candidates with backgrounds in data science, engineering, computer science, supply chain analytics or related quantitative disciplines, and an interest in applying advanced methods to real industry problems.

The student will be enrolled at Queen’s University Belfast, with flexible working arrangements over the four‑year programme. Travel to food manufacturing sites and engagement with industry partners will be encouraged, providing first‑hand exposure to real supply chain decision‑making. The student will also engage with wider academic–industrial innovation networks involving Samworth Brothers.

close partnership with Samworth Brothers, one of the UK’s leading food producers, the research will apply advanced data analytics and artificial intelligence to identify vulnerabilities and emerging risks across critical ingredient and supplier networks, with the aim of delivering near real‑time, decision ready insight.

The project offers an exceptional opportunity for a PhD student to work on a high impact, real world industrial challenge while developing cutting edge skills in AI, data analytics and risk modelling. The student will work with complex industrial datasets, collaborate directly with supply chain and technical specialists, and produce research with clear academic and commercial relevance.

The studentship is suitable for candidates with backgrounds in data science, engineering, computer science, supply chain analytics or related quantitative disciplines, and an interest in applying advanced methods to real industry problems.

The student will be enrolled at Queen’s University Belfast, with flexible working arrangements over the four‑year programme. Travel to food manufacturing sites and engagement with industry partners will be encouraged, providing first‑hand exposure to real supply chain decision‑making. The student will also engage with wider academic–industrial innovation networks involving Samworth Brothers.