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Ai & digital twin systems engineer (ktp associate)

Leicester
UAG
Systems engineer
€40,000 a year
Posted: 21h ago
Offer description

Contract Type: Fixed Term 28 months

The University of Derby’s engagement with global industries based in the Derby region helps ensure that our research and teaching are at the forefront of emerging industry needs and opportunities. Our links with companies in our region including Bloc Digital, Rolls‑Royce and Alstom, also mean our students benefit from placement years and live briefs.


About Richard Lang & Son Ltd

Founded in 1949, Richard Lang & Son Ltd is a third‑generation, family‑owned giftware importer and wholesaler based in Derby, supplying independent retailers and national chains across the UK, with expansion into Europe underway. As a heritage business undergoing significant digital and operational transformation, the company has invested heavily in warehouse modernisation, systems integration, automation, and enterprise data infrastructure.

The ambition is to architect and deploy scalable, production‑ready AI and digital twin systems that transform sales forecasting, inventory optimisation, supply chain performance, SKU profitability, and working capital efficiency, moving decisively from reactive management to predictive, data‑led operations.


About the Role

University of Derby’s College of Science and Engineering in partnership with Richard Lang & Son Ltd are offering an exciting career‑development opportunity to manage and deliver a challenging strategic Knowledge Transfer Partnership (KTP) project. Based at Richard Lang & Son’s premises in Derby, you will be employed by the University as a KTP Associate but work under the terms and conditions of the company.

You will lead the end‑to‑end design, development, and deployment of a scalable AI forecasting engine and digital twin platform, integrating advanced machine learning, simulation modelling, business intelligence, and real‑time data pipelines into RL’s operational environment.


Anticipated interview date: 11th June 2026


Knowledge Transfer Partnerships

This full‑time post is part‑funded by the UK Government’s KTP programme. A KTP is a three‑way project between a graduate, an organisation and a university. KTP is one of the UK’s largest graduate recruitment programmes and has been placing graduates on challenging, high‑profile projects for 50 years.

Please note by completing an application form for this role, you are giving your consent for us to share your personal data with the KTP partner.


About You

This role requires proven experience designing and building robust data engineering pipelines and delivering end‑to‑end AI or advanced analytics solutions. You will have experience applying digital twin modelling and simulation techniques to analyse, model, and optimise real‑world systems, and you’ll be confident using Python programming and SQL based relational databases to develop data workflows or machine learning applications.


Key Contact

For further information and informal enquiries regarding the role, please contact Dr Oluwarotimi W. Samuel, Senior Lecturer in Computer Science via o.samuel@derby.ac.uk or Dr Mojisola Grace Asogbon, Lecturer in Data Science via m.asogbon@derby.ac.uk.

For enquiries regarding your application and for sponsorship eligibility, please contact the recruitment team via recruitment@derby.ac.uk.


Important Information

This role may be eligible for sponsorship by the University.

The offered salary for this role is less than the going rate for the occupation and the minimum salary threshold for the Skilled Worker route (£41,700 per annum, as of 22nd July 2025). Therefore you will only be eligible to apply for a Skilled Worker visa subject to your individual circumstances which must meet one of the following criteria set out by UKVI: You must also meet the English Language requirement.

For more information and to apply on‑line, please click the “Apply” button above.

£38,000 to £40,000 per annum (for exceptional performers, there is scope for further progression up to £42,000 per annum)

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