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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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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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—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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-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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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
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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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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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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that