17 structures-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"LGEF" 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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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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ecological resilience and community wellbeing. You will quantify how spatial patterns, network structure and environmental context influence the capacity of blue spaces to provide co-benefits such as
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structure would enable you to understand science better at atomic level. You will learn the skills of presenting the results to small and large groups of people via presentations in conferences and meetings
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
carbon fibre-reinforced polymers (CFRPs), are increasingly adopted in structural applications due to their superior strength-to-weight ratios and fatigue resistance. However, their layered, anisotropic
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supported by the Enhanced Composite and Structures Centre at Cranfield. About the sponsor We will work in collaboration with Cambridge Nanosystems, which is a world leading high quality, high performance
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transformation in our IT and the business processes that support our research, student experience, education delivery and administration. You will have project management experience in a structured environment and
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, student experience, education delivery and administration. You will have project management experience in a structured environment and have a good appreciation of Agile and Lean best practice. You’ll also
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damaging or disassembling it is increasingly vital as electronic systems become more compact, critical, and opaque in their construction. This is especially relevant in sectors such as defence, aerospace
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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