Multi-Fidelity Digital Twins and Machine Learning for the Scale-Up of Flow Processes

The ‘what’ This PhD will develop multi-fidelity digital twin frameworks, integrating physics-based models and machine learning, to enable reliable scale-up of flow processes (e.g. in chemical, materials, and energy manufacturing). The ‘why’ Scaling up flow processes—from lab to pilot to industrial scale—remains one of the most costly and failure-prone stages in manufacturing. Small changes in flow behaviour, heat transfer, or reaction dynamics can lead to inefficiencies, safety risks, or product inconsistency. Digital twins offer a powerful route to predict and optimise performance, but current approaches are often either too computationally expensive (high-fidelity models) or insufficiently accurate (low-fidelity models). This project addresses a critical challenge: how to combine multiple model fidelities with machine learning to deliver fast, accurate, and scalable predictive tools. Success will accelerate innovation in sectors such as chemicals, energy, pharmaceuticals, and advanced materials—supporting more sustainable and efficient industrial processes.. The ‘who’ You will be based at Loughborough University, joining a multidisciplinary research environment spanning process engineering, AI, and computational modelling. You will be supervised by experts in digital manufacturing, fluid dynamics, and machine learning, with opportunities to collaborate across partner universities and research centres. Industry engagement and sponsorship The project is designed with strong industrial relevance and will involve collaboration with partners in process industries (e.g. pharma, chemicals, energy, or materials manufacturing). These partners can provide real-world datasets, case studies, and opportunities for industrial placement, ensuring that the developed digital twin frameworks address practical scale-up challenges. Aims and objectives Methodology (overview) The project will combine computational modelling, data-driven methods, and experimental validation: Skills and development You will gain expertise in: You will also develop transferable skills in interdisciplinary research, communication, and working with industrial stakeholders. Career pathways This PhD will prepare you for careers in: Why Loughborough With connections with MIT (Massachusetts Institute of Technology), Loughborough University offers a globally recognised research environment in advanced manufacturing, digital engineering, and intelligent systems. You will benefit from: 94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021

The standard University IELTS English language requirement is 6.5 overall with 6.0 in each individual element (reading, writing, listening and speaking).

International students: £29,500

UK students: £5,238

UK/Home: £5,238

International: £29,500

October 2026

31 July 2026

• Loughborough, United Kingdom