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Field
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state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material
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, with minimal computational cost. By developing an advanced reduced order modelling framework, this project will empower engineers and designers to achieve more with less—delivering high-impact decisions
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One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh. The broad aim
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required to have high performance, vacuum-based, insulation and integrate equipment capable of surviving this challenging environment. This adds weight and is one of the big challenges for aircraft
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performance will be assessed using finite element analysis and experimental work. Additionally, life cycle assessment will be performed to quantify environmental and economic impacts. This project is intended
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operating filters. Quantify operational performance including headloss recovery, filtrate turbidity, biological stability and lifecycle carbon—using high-resolution sensor data and life-cycle assessment tools
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highly efficient operation. TBCs are crucial to ensure the safe and high-performance operation of such critical parts under extreme temperatures and pressures; however, external contaminants (e.g. Calcium
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Laboratory), and will provide experience with new and advanced 3D-printing equipment not available elsewhere. This project is aligned with the “Dialling up Performance for on Demand Manufacturing” Programme
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. The start date is October 2025. Are you passionate about applying computational science to real-world engineering problems? Do you want to develop digital twins of materials that can predict performance and
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., Ni superalloy turbine blades) to ensure a reliable and highly efficient operation. TBCs are crucial to ensure the safe and high-performance operation of such critical parts under extreme temperatures