PhD studentship: System Digital Twin for Sustainable Olive Mill Waste Upcycling

University of Surrey - Chemical and Process Engineering

OLinWASTE is a recently funded €4 million EU Horizon project involving 10 consortium partners from 6 European countries. The project aims to revolutionize the biorefinery sector by pioneering an integrated zero-emission system and setting a new benchmark for sustainable innovation. This project will upcycle underutilized olive mill waste (OMW) into high-value products, including plant bioimmunostimulants, biopesticides, biofertilizers, biobased plastics, and bioenergy. Key focuses include reducing greenhouse gas emissions, optimizing exhaust flows, minimizing noise, recovering thermal energy, and reducing odors from pomace and digestate.

The project comprises seven work packages. As a leading partner, the University of Surrey will develop a system digital twin (SDT) to enhance overall sustainability, efficiency, and the optimization of material, energy, and waste flows.

The main tasks include:

• Developing Digital Twins: Using data from other work packages, create digital twins (DTs) for waste treatment processes through advanced machine learning, validated against physics-based models and experimental data.
• System Integration: Integrating the DTs into material and energy balance equations to develop an SDT that simulates real-time system operation in a dynamic virtual environment.
• Online Implementation: Deploying the SDT on an evolving online platform, continuously updated with new data and novel multi-objective optimization algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint.

The University of Surrey is ranked 12th in the UK in the 2025 Complete University Guide and was awarded The University of the Year for Graduate Employment in 2021. The Surrey Circular Economy group (www.surrey.ac.uk/surrey-circular-economy-group) and the main supervisor Dr Lei Xing has built a strong track record in circular chemical economy, green energy, carbon capture and utilization, AI and digitalization.

Supervisors: Dr Lei Xing and Professor Jin Xuan

Entry requirements: Open to any UK or international candidates. Starting in January 2026. You will need to meet the minimum entry requirements for the PhD programme. By the start of the PhD programme, applicants must be awarded a master’s degree in Chemical Engineering, Physics, Mechanical Engineering, Energy Engineering, Environmental Engineering, Computer Science, or other related disciplines. Applicants with track records or experience in system modelling, machine learning and control are highly desirable.

How to apply: Applications should be submitted via the Chemical and Process Engineering Research PhD programme page.

Funding: Fully and directly funded for this project only, funding available for 36 months/3 years. This studentship will cover the tuition fee and a tax-free stipend for three years. Stipend at UKRI rates for 2025-26 is £20,780. Qualified candidates will also be supported to attend professional trainings and domestic/international conferences.

Application deadline: 6 October 2025. Start date: January 2026. Enquiries: Contact Dr Lei Xing. Ref: PGR-2425-062.