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Field
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). Robotics and Autonomous Systems (RAS) is an essential enabling technology for the Net Zero transition in the UK’s energy sector. However, significant technological and cultural barriers are limiting its
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an annual tax free stipend set at the UKRI rate (£20,780 for 2025/26) and the tuition fees will be paid. We expect the stipend to increase each year. Delivering Net Zero will require not only deep emissions
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performance of industrial systems (up to 100 MW+). You will receive specialist training through the Engineering Hydrogen Net Zero CDT and be based at Loughborough University. Primary supervisor Sonya Calnan is
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growing number of PhD students working on the transition to net zero. This project forms part of a collaborative relationship with the Institute of Economics within the Department of Business Science at
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the integrated framework for high-risk commodities like edible oils, spices, and herbal supplements. The project is jointly funded by UEA and CAMS-UK (Community for Analytical Measurement Science). It will also
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The Child and adolescent Health Impacts of Learning Indoor environments under net zero (CHILI) Hub is a program funded by the MRC and NIHR, the goal of which is to understand the health effects we
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the evidence–base needed to understand the impact on health, to inform public policy, and to develop potential mitigation strategies. Traditionally, this information has come from ground monitoring networks
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 2 months ago
support UK industry to reach net zero. Alongside their research, our PhD researchers gain valuable training in how to apply their research within the wider industrial system, including opportunities
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sleep patterns, gaining insights into sleep-related issues, and personalised sleep health management. However, the dynamic nature of sensor networks caused by frequently adding and removing nodes has
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-informed data analytics tools for the predictive maintenance (PdM) strategy applications to high-value critical assets. Among others, the recently developed Physics-informed Neural Network (PINN) technique