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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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PhD studentship: Improving reliability of medical processes using system modelling and Artificial Intelligence techniques Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience
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. Ying Weng is Course Director for Computer Science with Artificial Intelligence, Professor in Computer Science. She obtained PhD in Signal & Information Processing at Chinese Academy of Sciences, and
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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opportunities for collaboration. About You The candidate must have obtained a PhD degree within 3 years and in the areas of Applied Psychology, Management, Statistics, Artificial Intelligence; Excellent oral and
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and its stakeholders. You should hold a Master’s or PhD (desirable) in Computer Science, Artificial Intelligence, Machine Learning or a closely related field. We are looking for a candidate who has
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Manufacturing process for Cold Spray with Artificial Intelligence, operate the AM machine, characterise the materials with scanning electron microscopy and transmission electron microscopy with tensile testing