Senior Research Associate

Position

SeniorResearchAssociate-AdvancedAIModelsandOptimisation Algorithms for Supply ChainPlanning and Scheduling

Department: Business School

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

Salary: Specialist and Supporting Academic Research grade 7 from £47,389

About the University

Universities are one of this country's greatest assets.We'reeducators, employers,innovatorsand pioneers. We shape culture and society.

At Loughborough, we strive for better, think differently, challenge convention andtake action. We are passionate about finding solutions to the major problems faced by society and the planet, and we create opportunities for those with the drive, the ambition, and the determination to apply themselvesin the pursuit of better.

About Loughborough Business School

We area vibrant,research ledschool with a strong reputationfor academic excellence,real worldimpact 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 () for its leadership in responsible management education. TheSchoolalsoholds Small Business Charter accreditation and a Bronze Athena Swan Award, reflecting its commitment to entrepreneurship,equalityand positive societal impact, and offers a supportive andforward lookingenvironment in which staff and students can thrive.

About the role

This project, Smart Slots: AI-NativeFactory 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 optimisation algorithms that integrate carbon and productivity objectives into factory planning and scheduling.

Key responsibilities

• Develop, analyse, and implement AI-based solutions, analytical modelling, and optimisation methods for production and supply chain planning in SMEs.
• Integrate carbon and productivity objectives into scheduling models and software products of an industry technology partner.
• Work closely with academic colleagues and industry partners to ensure models are robust, usable, and aligned with real world manufacturing contexts.
• Contribute to software development within the project team.

Qualifications and experience

• Expertise in advanced AI, machine learning, generative AI, LLMs, agentic AI, and optimisation models.
• Experience in developing models for production and supply chain planning, especially in SME manufacturing contexts.
• Strong analytical and software development skills.
• Ability to collaborate with academic and industry stakeholders.

Benefits

• Time off - generous holiday allowance, including 14 university closure days and bank holidays, with the option to buy extra through our holiday purchase scheme.
• Where you work - access to a range of fantastic facilities with plenty of green space across our 523 acre East Midlands campus, plus an exciting community at our London campus on the Queen Elizabeth Olympic Park.
• Financial Wellbeing - competitive pay, two excellent pension schemes, and everyday savings opportunities.
• Support for you and those close to you - through our range of life event leave policies as well as access to an on site nursery at our East Midlands campus, flexible and hybrid working options.
• Health and Wellbeing - discounted gym memberships and access to world class sporting facilities, including physiotherapy, plus healthcare offers such as eyesight testing and wellbeing support.
• Travel and sustainability - access to our electric vehicle and cycle to work schemes, as well as a variety of travel offers to support sustainable commuting.

If this sounds like the right place and role for you please do get in touch. We'd love to hear from you.

We are happy to consider any reasonable adjustments that candidates may need during the recruitment process. If there are additional adjustments you'd like to request, please contact Professor Shahin Rahimifard. We also offer reasonable adjustments on the job.

Loughborough University is a fantastic place to work and we're proud of our welcoming, supportive, and successful academic community.