33 computer-security "https:" "https:" "https:" "https:" "https:" "Dr" "Keele University" scholarships at Cranfield University
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detection of chemical and microbial contaminants in rivers. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme, which is supporting new research
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contact Dr Muhammad Khan for an initial informal discussion about this opportunity. Please include the keyword PhD Studentship-Self Funding in the subject field. If you are eligible to apply
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are part of the programme. Entry requirements Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit students with an aerospace
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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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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the world within a range of industrial and commercial sectors. These are Water, Agrifood, Energy and Power, Aerospace, Manufacturing, transport systems, Defence and Security and management.
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, autonomous systems, and secure intelligent hardware. Through collaborations with the Aerospace Integration Research Centre (AIRC), Airbus, and Rolls-Royce, students gain industry exposure and further research
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will handle real human waste samples to develop robust protocols for solid and liquid waste characterization, microbial profiling, and safety validation, including pathogen screening. Focus areas include
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves