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Field
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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and programmable biomaterial synthesis. The ability to program the behaviour of biomolecular chemistry is foundational for developing new biotechnology applications. Redox-sensitive molecules are a
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on developing your core research skills Programme flexibility with the introduction of study tracks to tailor your studies, supported by a wide range of research groups The opportunity to develop a global network
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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. Changes in water table pre- and post-restoration will be monitored using the existing network of piezometers distributed across the floodplain and additional piezometers installed. Additional measurements
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inaccurate, and rain gauge networks, while reliable, are too sparse to capture highly localised storms. Reliable, high-resolution rainfall data is urgently needed to improve flood prediction, climate
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microclimates that demand dense sensor networks and reliable data retrieval. This project focuses on developing nature-inspired hardware to deploy Internet of Things (IoT) sensors in forest ecosystems. Combining
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Mission-Inspired priorities of Engineering Net Zero and Artificial Intelligence. This vision also reflects RCA’s institutional research priorities: Climate Crisis and the Circular Economy, and Design & AI
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the University of Nottingham, contributing to cutting edge research into clean and sustainable energy technologies. Vision and Aim Ammonia is an essential component of the global strategy to achieve net-zero