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Field
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population-based studies. Using data from 11 million vessel segments from over 200,000 CFPs, we have shown that retinal vasculometry can predict cardiovascular disease as well as established risk scores and
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This self-funded PhD opportunity focuses on assured multi-domain positioning, navigation, and timing (PNT), integrating data from space-based, terrestrial and platform-based sources of navigation
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Grand Tours, one-day races (monuments and semi-classics), and select World Tour 1-week stage races. The data sources will include video and previous race commentary to ‘code’ key events in races that help
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sensors to deliver resilient, high-accuracy positioning. The project sits at the intersection of navigation, AI-enhanced signal and data analysis, and wireless communication systems, with applications in
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English language requirements. Further details are available on the International website . Funding information: The studentship is for three years and provides a tax-free stipend of £20,780 per annum
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of this project, please contact Prof. Tony McNally (T.McNally@warwick.ac.uk ) directly for further information. Essential and Desirable Criteria: 1 or 2.1 degree in Materials Science & Engineering, Chemical
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myriad of new techniques and much sought-after skills demanded by industry, including the following: Design of experiments, data harvesting/analysis and interpretation of results to derive insight
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countries, and will contribute to UK higher education and research by attracting high-calibre international candidates and encouraging links and collaboration, and are aimed at those who could not otherwise
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the PhD student in high-performance computing, computer programming, applied mathematics, fluid mechanics, mathematical modelling and data analysis for large datasets -of the order of 100 Terabytes
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motion and the viewing perspective of the observer (Nikolaidis et al, 2016). This project will develop continuous models of action legibility using these sources of information from data collected in a