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. Overview This project is part of the EPSRC Centre for Doctoral Training in Process Industries: Net Zero (PINZ) . The aim of the PINZ CDT is to train the next generation of chemical engineers and chemists
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excellent’ (3*) while 90% of its research has been classified as having ‘outstanding’ (4*) or ‘very considerable’ (3*) impact. The Centre for Engineering Research and the Network and Security Research Centre
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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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. 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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https://www.sems.qmul.ac.uk/research/studentships/674/net-zero-natural-resource-energy-and-time-efficient-manufacturing/The PhD work will benefit from access to unique facilities including
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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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models such as Random Forest and Neural Networks to help understand and predict pairwise interactions between pollinators and plant species. - Software Engineering: integrate models into a standalone
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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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(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
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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