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Field
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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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networks which are intrinsically explainable; (5) design a new multi-dataset benchmark for assessing the trade-off between accuracy and explainability Project Description: Whereas traditional machine
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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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research and impact related to two EPSRC-funded projects: ResTOrES (Resilience Toolkit for Offshore Energy Systems) and RENEW (Climate Resilient Heat Electrification for Net-Zero Emission Whole Energy). The
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South and East Network for Social Sciences (SENSS) and CAM-DTP are pleased to announce a call for two ESRC-funded studentships. The purpose of this joint scheme is to promote collaboration between
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real-world challenges. We work with an extensive network of industrial partners including BT, Haleon and Tesco. Engage with our network of charitable partners Students have the opportunity to engage with
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Research Group) Aim: Model and analyse component and system level reliability, availability and resilience of hydrogen systems Background Driven by climate change concerns and net-zero carbon targets, in
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management experience across multiple industries, build an extensive professional network spanning academia and industry, and cultivate commercial awareness that enhances your career prospects. Alumni from
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to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail, Schlumberger and Alstom. Entry requirements Applicants should have a first or
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. The research will probe beneath surfaces to detect impurities and internal features, while also exploring new methods for embedding invisible authenticity markers. Finally, advanced data tools and neural network