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@UT). The research combines manufacturing systems engineering, digital factory modelling, and sustainability assessment, and includes validation through industrial case studies and demonstrators. By
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modelling, data-driven approaches, and experimental validation. The project combines computational materials science with practical membrane design for electrochemical energy applications. PhD Position 1
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before the deadline. Computational haemodynamic modelling provides a powerful framework for linking blood flow dynamics with cardiovascular disease, using in silico approaches to systematically study flow
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Compliance Engine to embed regulatory rules into the digital twin environment. Project Timeline Year 1 (Month 1-12): WP1 and associated training to obtain core skills in digital twin modeling and adversarial
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, we explore how value-driven tools can help practitioners and policymakers navigate value tensions that arise at the intersection of multiple transitions. One of the aims of the project is to develop a
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receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to increase each year. Computational haemodynamic modelling provides a
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computational modelling and non-invasive brain stimulation. The focus of this project will be on advanced versions of transcranial alternating current stimulation (tACS), targeting multiple brain areas in
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behaviour across multiple physical models. As the PhD researcher on this project, you will work at the intersection of machine learning, geometry processing and industrial simulation. You will have the
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workflows rely heavily on geometric de-featuring, an expert-driven, manual, and time-consuming process used to simplify CAD models so that meshing tools can cope with small-scale features such as fillets and
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, and mineralogy Independent, self‑driven researcher with a strong problem‑solving mindset Proven team player, able to collaborate across multiple institutions Critical thinking to assess model