51 structural-engineering "https:" "https:" "https:" "https:" "https:" "https:" "Multiple" scholarships at Cranfield University
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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
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reusable launchers, autonomous robotics, and advanced materials could redefine how we design space structures. The ability to remotely assemble orbital systems from multiple launcher payloads would allow
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solutions. You will study the collaboration and coordination processes that enable successful technology development across international partnerships. This research combines hands-on engagement with advanced
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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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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
Design and manufacturing engineering represents the critical bridge between innovative concepts and real-world implementation, particularly in global sanitation technology where products must be
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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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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient