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and signal processing methods using machine learning techniques to enhance the resilience, efficiency, and security of cell-free massive MIMO systems, which are expected to play a key role in next
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develop novel approaches that integrate uncertainty estimation and confidence-aware predictions, enabling models not only to classify species but also to quantify their reliability. Such methods are crucial
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on health and use economic methods to evaluate relative costs and benefits. This may include use of health impact assessment methods, statistical analysis of secondary data sources to estimate health impacts
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Award Summary Full PhD tuition fees at the UK home student rate (UK students and EU students with settled or pre-settled status). An annual stipend equivalent to the UKRI doctoral stipend (estimated
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tackling the above challenges with novel system designs and tailored AI/ML based methods. Candidate’s profile A First Class Bachelors degree and/or Masters degree in a relevant subject (computer
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to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
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the combined themes of human-computer interaction and critical computing. The lab will be exploring the notion of "deceptive by design" on all fronts: social identity cues in the design of LLM-based chatbots
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effective diagnostic methods and treatment protocols. The overall purpose of this research project is to identify biomarkers and develop effective antimicrobial strategies to prevent infection and
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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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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