45 structural-engineering-"https:"-"https:"-"https:" PhD positions at Cranfield University
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project will develop novel methods for modelling and controlling large space structures (LSSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. Working with leading
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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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The research in this doctoral opportunity will analytical and numerically model the changes in modal responses of a structure under thermo-mechanical loads. Sub-surface fatigue in mechanical
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performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
time, and enhance safety in aerospace, defence, and automotive sectors. The project contributes to digital engineering and sustainability by improving structural health monitoring and extending component
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of first or second class UK honours degree or equivalent in a related discipline, science (chemistry/physics) or engineering. The ideal candidate should have some understanding in the area of materials
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protection, will also benefit from collaboration with The Structural Battery Company, a leader in structural battery technology solutions for EV applications, ensuring industry relevance and direct
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years EligibilityUK, EU, Rest of world Reference numberSATM450 About the host University and Through-life Engineering Services (TES) Centre Cranfield is an exclusively postgraduate university that is a
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technologies. Metamaterials, engineered to exhibit properties not found in naturally occurring materials, offer an innovative pathway to overcome these limitations. By designing intricate periodic or quasi
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structure, stage-structured demography and density dependence, road-crossing mortality, and climate–hydrology drivers to predict population trajectories and evaluate mitigation scenarios. This PhD will equip