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support from leading experts in Advanced Sensor Technology Research Group and Environmental Assessment Facilities at Cranfield University. This fully funded studentship is part of the Connected Waters
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, Sustainability Studies, Business (with a focus on environmental risks), Water or Civil Engineering, or other related social science degrees. It is essential that candidates have experience of, or a good
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This is a self-funded PhD position to work with Dr Adnan Syed in the Surface Engineering and Precision Centre. The PhD project will focus studying high temperature corrosion mechanisms in details
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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discipline. This project would suit someone with interests in ecology, environmental science, urban sustainability, geospatial analysis, or quantitative modelling. Experience in all areas is not required as
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facilities, along with support from leading experts in Advanced Sensor Technology Research Group and Environmental Assessment Facilities at Cranfield University. This fully funded studentship is part of
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range of future careers. Should there be interest, there is also the possibility of developing teaching and supervision skills on our MSc Astronautics and Space Engineering programme. At a glance
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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Start date: 28/09/2026 Fee status: UK Duration *: 4 years 1st Supervisor: Dr Simon Jude 2nd Supervisor: Dr Robert Grabowski This funded PhD studentship is an exciting opportunity to conduct new
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Start date: 28/09/2026 Fee status: UK Duration *: 4 years 1st Supervisor: Alice Johnston 2nd Supervisor: Robert Grabowski This project is to investigate how urban blue networks can be optimised