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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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net zero aviation. This project will explore the science of novel cooling technologies, such as phase change materials and heat transfer enhancement, for the air systems used to condition the turbine
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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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-on experience in environmental management. Interdisciplinary training in hydrogeology, contaminant transport modeling, and decision-making. Networking & knowledge exchange with leading academic and industry
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with a wide network of stakeholders, and explore new avenues for medical applications. For ongoing work and publications on this project, please see our website: www.cnnp-lab.com . This is a 12-months
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for the ‘Course Title’ using the programme code: 8856F Leave the ‘Research Area’ blank Select ‘PhD in Process Industries; Net Zero (PINZ’) as the programme of study You will then need to provide the following
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optimization techniques, coding new algorithms, creating new mathematical theory, and the analysis of large data ensembles. You will write papers for submission to academic journals, collaborate with academics
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significantly reduce carbon emissions and bolster global efforts to achieve net-zero targets. Despite considerable advancement in their operational performance, their life cycle impacts, including raw material
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the need for sustainability to achieve Net-Zero goals. Cyber-Physical Systems (CPS) integrate machines, robots, and AGVs, but challenges like mechanical wear and electronic errors pose risks to efficiency