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engineering, clinical research, and AI-driven health monitoring. This project will explore large-scale maternal datasets—combining clinical cardiovascular assessments with wearable sensor data—to detect early
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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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), the Quadram Institute and Newcastle University. The unit undertakes research aimed at protecting the health of the UK population from gastrointestinal infections common in the UK such as E. coli, Salmonella
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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-critical decisions in real time. These systems rely heavily on sensor data (e.g., GPS, pressure transducers, image processors), making them vulnerable to stealthy threats like False Data Injection (FDI) and
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mapping using a team of highly mobile legged or legged-wheeled robotic platforms. The research will investigate advanced algorithms for multi-robot coordination, dynamic path optimization, and collaborative
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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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for long-term monitoring to confirm successful restoration5. This exciting and timely PhD will develop and deploy a range of low-cost and open-source sensors to measure the biophysical properties necessary
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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needs. By bridging human-centric innovation, generative algorithms, and sustainability metrics, this project seeks to redefine how novel products and systems are conceived, developed, and evaluated. You