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Overview: This exciting PhD opportunity is at the intersection of aerospace engineering and cutting-edge technology. It focuses on developing an innovative ground-based robotic inspection system
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PhD Studentship Aircraft Electrical Power System Stability This exciting opportunity is based within the Power Electronics and Machines Centre (PEMC) Research Group at Faculty of Engineering which
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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for success: A PhD awarded in a relevant discipline e.g. social sciences, history, science and technology studies, anthropology, or other discipline with a strong background in conducting qualitative research
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candidates will have a PhD (or equivalent experience) in Computer Science, electrical engineering, or other related quantitative subject. They will have a strong understanding of computer science (hardware and
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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@manchester.ac.uk . Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.
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specification: • BEng/MEng in Engineering discipline with appropriate energy and data modules, particularly Chemical Engineering, Mechanical Engineering, Electrical Engineering, Energy Engineering (minimum of 2:1
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performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power
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Tomography (ToF-PET) offers vital functional and molecular insights for improved cancer staging, its current capabilities are often limited by the timing resolution and sensitivity of existing detector