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Field
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the low volumetric density of hydrogen, ammonia has emerged as a promising hydrogen carrier and zero-carbon fuel. The overall aim is to develop a novel direct ammonia fuel cell technology that can
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physics-informed neural networks (PINNs). However, these approaches are still in their early stages of development and have yet to demonstrate their effectiveness for complex real engineering problems
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Applications are invited for an EPSRC Industrial Doctoral Landscape Awards (IDLA) PhD position at the University of Nottingham addressing the specific engineering details of the wear of articulating
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the menstrual cycle. In this project you will combine innovative smart technology and the latest AI-based food tracking apps to understand the impact of dietary behaviours on PMS and perimenopausal symptoms and
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directly with speaker communities to ensure the technology is genuinely useful to them. You will gain deep expertise in machine learning and natural language processing, access to high-performance computing
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, mathematics, engineering, or a closely related discipline. Essential A solid foundation in at least one of cryptography, network security, post-quantum or quantum cryptography, with enthusiasm to build
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of the most dynamic environmental conditions. Understanding how these offshore aquaculture systems respond to waves, currents, and extreme storms is one of the key engineering challenges of the next
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to obtain, undergraduate and preferably a postgraduate qualification in computer science, artificial intelligence, data science, environmental modelling, coastal engineering, geography, or a related
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measurement data. The project combines fundamental research with practical engineering challenges, offering opportunities to contribute to technologies with real-world industrial impact. This project provides
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Research theme: AI for Engineering How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded; students who are eligible to pay tuition fees at the Home rate are eligible