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improvements in machine learning (ML) applications now allow researchers without extensive programming backgrounds to implement advanced image-processing techniques using accessible programming languages and
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frameworks. This approach is timely, as improvements in machine learning (ML) applications now allow researchers without extensive programming backgrounds to implement advanced image-processing techniques
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Supervisors: Prof Ioan Notingher (School of Physics and Astronomy) Dr George Gordon and Dr Abdelkhalick Mohammad (Faculty of Engineering) Funding: fully-funded (stipend and PhD fees) Start date
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@ddrc.org) 3rd Supervisor: Dr Elsa Fouragnan (elsa.fouragnan@plymouth.ac.uk) 4th Supervisor: Dr Helen McKenna (helen.mckenna@plymouth.ac.uk) Applications are invited for a fully funded 3-year PhD studentship
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above 'Apply' button), to create your account, and use the link sent by email to start the application process. During the application process, please select ‘PhD in Law’. *Important notes* Please quote
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methodology to generate confidence in such decision, potentially reducing maintenance costs and down-time for offshore wind energy production. The images taken by each drone are loaded into the pre-processing
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composition and microstructure of the alloys has to be tightly controlled as impurities during processing forms damaging microstructural defects and secondary phases. It is possible to add refiners and
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speed - Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace
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Fully funded 4-year PhD studentship in Computational Chemistry Supervisor: Dr Zsuzsanna Koczor-Benda, UKRI Future Leaders Fellow (FLF) We are looking for a highly motivated and talented PhD
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, using signal processing/machine learning techniques, to realise all-weather perception in autonomous vehicles with high-quality multiple-input-multiple-output (MIMO) radar sensing/imaging. The project