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Discipline: Engineering & Technology, Fluid Dynamics, Mechanical Engineering, Other Engineering Research area and project description: Droplets are ubiquitous in nature, industry, and our everyday
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School/Faculty: Computer Science Eligibility: UK/International Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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including the newly established Quantum Hub in Sensing, Imaging and Timing (QuSIT) and a newly awarded Royal Academy of Engineering (RAEng) Research Chair on multistatic radar systems. Finally, it will
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student with an aerospace, mechanical engineering, or physics background. Experience of experimental and computational modelling of icing physics, instrumentation and imaging techniques would be
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. What the research involves: The project work will involve deliberately contaminating engineering alloy plates with varying quantities of contaminants such as copper or zinc. Single-pass welds will be
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based
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the growing demand for sustainable AI-enabled systems, this PhD brings together low-power computing, energy-aware design, and thermal optimisation. You’ll work with advanced profiling tools, prototype long-life
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create a computational tool based on experimental input, simulated data, and machine learning methodology to extract 3D atomic structure information from 2D identical location STEM images. STEM image data
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or sensor arrays. Experience generating, processing and analysing large material property datasets including correlating between multiple techniques, or developing computational reconstruction techniques