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Field
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technological advances that support the global transition toward net-zero emissions and sustainable aerospace engineering. Motivation The reliability of electric propulsion systems is pivotal for next-generation
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construction of creek networks to ensure the transfer of water, sediment and nutrients around the site. However, the current approach to site design involves the use of pre-existing agricultural drainage ditches
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challenges in high-speed electrical machine design for electrified transportation and power generation. Together, we will make technological advances that support the global transition toward net-zero
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, University of London in August 2024. As a PhD candidate, you'll become an integral part of the School of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading
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techniques. We are a community based on mutual support and collaboration. Through our Doctoral College there are continual opportunities for building important research skills and networking among your peers
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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) under the supervision of Dr. Elina Spyrou . Summary of Project: Power systems are at the core of the transition to net-zero energy systems, and they have to transform in two ways. First, their generation
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services would be to keep children close to their usual home (where safe to do so) and maintain their family and community networks often this is not possible and high cost out of area placements
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isolation, leading to suboptimal network performance. This project seeks to address this gap by developing a holistic, system-level approach that optimises PST deployment strategies to enhance grid
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of HDR UK-funded PhD students, with outstanding networking opportunities with fellow students and colleagues located across the 4 nations of the UK. HDR UK’s mission is to unite the UK’s health data