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impacts and suboptimal decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport
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to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated into smaller, faster, more energy efficient and cost-effective hardware
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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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of Oxford. The post is funded by United Kingdom Research and Innovation (UKRI) and is for 24 months. The researcher will develop 3D mapping and reconstruction algorithms with relevance to mobile robotics
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data are needed to enhance our understanding of sources, pathways and impact of litter. Cefas is developing a visible light (VL) deep learning (DL) algorithm and collected a large 89 litter category
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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are categorised as non-destructive testing techniques, but they can be costly considering the number of sensors required and the maintenance of the data acquisition system. Hence, the alternative of direct
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, despite its widespread application, polygraph data capture and analysis has received limited systematic research and does not yet incorporate modern sensors, computing and analytical techniques. Project
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algorithms using Monte Carlo simulation and Bayesian inference to distinguish normal tritium losses from suspicious discrepancies during transport, and to develop statistical thresholds that balance detection