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Field
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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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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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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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of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health
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models considering networks of patches and their species and interactions composition to predict spatial and temporal community structure across restoration gradients, aimed at developing a predictive
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modelling software. Practical experience in advanced manufacturing techniques for novel materials. Opportunities to present research at international conferences and build a professional network across
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to reach carbon net zero by 2050. Between 40 to 50% of the carbon footprint of a litre of milk is attributed to CH4 production in the rumen (Huhtanen et al., 2022) which also has a negative impact on animal
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professional network spanning academia, industry, and national research centres. Through this multidisciplinary project, the student will develop expertise in: Contribute to the development and operation of
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Cyber-Physical Power Systems Research area and project description: This is an exciting PhD project to be carried out in close collaboration with a UK electrical network operator and an industrial co
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be carried out under the UK Hypersonics Doctoral Network, which has been supported by the Ministry of Defence and EPSRC for building the necessary expertise to develop next-generation hypersonic