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Field
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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative
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energy efficiency. Surface treatments and engineered coatings will be explored to improve inter-material interfaces, reduce optical losses, and enhance detector robustness, critical factors to advance
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electronics is essential, while prior knowledge of optical or laser systems is desirable but not essential. Applicants should have a strong interest in applied research, be motivated to work on the practical
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, this project will further investigate the optical and thermophysical properties of ceramic moulds—critical for predicting heat flux during casting and improving microstructural integrity. The work will explore
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engage in immersive, simulated construction tasks, while wearable sensors monitor their physical effort, emotional states, and cognitive load. Physiological and behavioural data — including eye tracking
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altitude could modify the optical or physical properties of cirrus, but we are currently limited by a lack of observational data. This project will fill that gap, using existing aircraft and satellite
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propellants potentially pose a risk during the proximity operations a kick stage would undertake, for example, condensing on sensitive surfaces such as solar arrays and optical or other sensors
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global warming, but it remains unclear whether it would be effective in practice. CCM relies on the idea that emitting small amounts of aerosols at high altitude could modify the optical or physical
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brightfield/darkfield optical microscopy and spectroscopy, optical lithography/patterning, hyperspectral imaging, photocurrent measurements, and sensor characterisation with suitable readout electronics
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implement novel forms of biophysical instrumentation (e.g. advanced optical tweezers and magnetic tweezers, single-molecule fluorescence, novel single-molecule approaches to DNA sequencing, integration with