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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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procedures. These systems combine preoperative planning and intraoperative measurements into a visual interface, improving surgical precision and outcomes. However, current navigation methods have significant
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emerging photonic microdevices promising to revolutionise computer, communication, and sensing technologies must be performed with unprecedented picometre (one-hundredth of the atomic size) precision
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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project aims to address the knowledge gap by investigating: - How ML methods can be adapted for complex, real-world conditions, including noise and interference, - How such methods can be
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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would co-develop the research objectives and select the methods to be implemented with supervisory support. Some ideas to discuss include integrating repeat GEDI LiDAR surveys with time-series
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is to explore and use available data sources to estimate prevalence of key infections (tuberculosis, HIV, hepatitis B virus (HBV) and hepatitis C virus (HCV)) among migrants to high-income countries
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. The developed technology will be rooted in causal reasoning, and we envision leveraging causal generative AI methods to develop a rigorous and comprehensive AI testbed. Clinical applications include, but are not
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute