"KTP Associate - Operational Researcher"

Are you a recent postgraduate eager to shape the future of environmental services through cutting-edge AI?

The University of Surrey, in collaboration with Whitespace Work Software Ltd - the UK’s market leader in environmental software - is recruiting a passionate operational researcher for a transformative Knowledge Transfer Partnership (KTP) project.

This strategic initiative will support Whitespace’s evolution into a fully integrated, AI-powered municipal resource management solution provider for smart city local authorities, accelerating the transition to a circular economy. Whitespace currently supports over 130 local authorities and public sector contractors with scalable future-ready technology. This KTP reflects Whitespace’s ongoing commitment to innovation, people, and long-term partnership with the University.

The Role

As one of two KTP Associates, you’ll be based at Whitespace’s headquarters in Godalming, co-leading the development of a data-driven platform to optimise recoverable assets collection routes. Working within the company, you’ll work alongside a second Associate and be supported by academic experts from the University of Surrey, including:

• Dr Abdolreza Roshani and Dr Wolfgang Garn (Surrey Business School)
• Dr Yinglong He (School of Engineering)

KTP provides a unique opportunity to apply knowledge gained through academic study in a real-world setting, helping bring an innovative solution to market while launching your career in industry.

The Candidate

We’re looking for a highly motivated and results-driven individual with a postgraduate degree in one of the following:

• Operational Research
• Applied Mathematics
• Computer Science
• Business Analytics
• A related quantitative field

You will also bring experience in:

• Optimisation algorithms (exact methods and heuristics),
• Strong understanding of routing algorithms (e.g., Dijkstra, A*) and graph theory,
• Preferably knowledgeable in the Arc Routing Problem, Vehicle Routing Problem, Rural Postman Problem, Travelling Salesman Problem, etc.,
• Preferably a good understanding in machine learning, natural language processing and AI,
• Preferably, a background in data-driven research and high-performance computing,
• BI/Data Visualisation (Power BI),
• SQL and cloud-based databases (preferably with GIS, e.g., postGIS), and
• Project management and business acumen - including mapping business processes, presenting insights, and translating technical concepts for non-technical audiences.

You will thrive in a collaborative environment, be energised by learning new technologies, and have a genuine passion for driving innovation through integration of predictive machine learning models with advanced optimisation techniques to solve a complex, real-world problem—dynamic route planning for urban waste management.

This 24-month fixed-term contract offers exceptional benefits:

• Hands-on Business-based experience leading a high-impact project in a commercial setting.
• Mentorship from academic and industry experts.
• Generous, dedicated personal development budget and dedicated time for training.
• Potential for a permanent role at Whitespace upon successful completion of the KTP project.

Informal enquiries are welcomed and can be directed to Dan Bance at: ilovektp@surrey.ac.uk. Please note applications sent directly to this email address cannot be accepted.

As part of the Knowledge Transfer Partnership (KTP) Programme, your application will be reviewed by representatives from both the University of Surrey and the host organisation, the Business Partner. By submitting your application, you consent to your personal details being shared with the business partner for the purposes of recruitment and project delivery.

To ensure you're considered for this opportunity, we encourage you to apply as early as possible. Please note that we reserve the right to close this advertisement ahead of the deadline if we receive a high volume of strong applications. This role is subject to completion of contractual terms between all associated parties.

Further details

Job Description