Senior Research Associate - Advanced AI Models and Optimisation Algorithms for Supply Chain Planning and Scheduling

Full Time and Fixed Term for 9 months (Subject to Funding)

About Loughborough Business School

We are a vibrant, research-led school with a strong reputation for academic excellence, real-world impact and an inclusive, collaborative culture. It is among an elite global group of business schools to hold triple accreditation from AACSB, EQUIS and AMBA, and was named a PRME Champion (2024–2025) for its leadership in responsible management education. The School also holds Small Business Charter accreditation and a Bronze Athena Swan Award, reflecting its commitment to entrepreneurship, equality and positive societal impact, and offers a supportive and forward-looking environment in which staff and students can thrive.

Here’s more about the role and what we’re looking for:

This project, Smart Slots: AI-Native Factory Scheduling for SMEs, is based at Loughborough Business School and addresses the challenge of helping manufacturers meet the UK’s Net Zero 2050 commitment while improving productivity and reducing waste. Funded by Innovate UK, the project is led by Dr Kamran Ali Chatha, Dr Grammatoula Papaioannou and Professor Jan Godsell, working in close collaboration with an industrial technology partner specialising in supply chain planning and manufacturing decision-support software, alongside a network of SME manufacturing collaborators.

The project aims to develop advanced AI (machine learning, generative AI, LLMs, and agentic AI) based models and optimization algorithms that integrate carbon and productivity objectives into factory planning and scheduling. The post holder will be an integral member of the project team, contributing to developing AI based solutions, analytical modelling, and optimisation methods, and software development, while working closely with academic colleagues and industry partners to ensure practical relevance and impact for SMEs.

The post holder will develop, analyse and implement solutions, using machine learning, generative AI, LLMs, and agentic AI and optimisation models for production and supply chain planning in SMEs, with a particular focus on their integration into the software products of an industry technology partner. They will work closely with academic and industry collaborators to ensure models are robust, usable and aligned with real-world manufacturing contexts.

Informal enquiries should be directed to Dr Grammatoula Papaioannou at G.Papaioannou@lboro.ac.uk or Dr Kamran Ali Chatha at K.Chatha@lboro.ac.uk.

For more information refer to the Job Description and Person Specification.

Closing Date: 18 June 2026

Interview Date: 29 June 2026