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Modern deep learning techniques achieve human-like performance in many medical image analysis tasks, including the identification of anomalous tissue/pathology from medical scans. To be trained
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or electronic engineering, machine learning, medical physics or neuroscience. Knowledge of electronics is essential. Strong programming skills (MATLAB is essential) & Phyton (TensorFlow library, desirable
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students are eligible to apply but will be required to make up the difference between home and international fees. Overview Are you interested in physical activity and keen to bring together different
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of Photonic Technologies to be undertaken within the College of Engineering and Physical Sciences at Aston University. Financial Support This studentship includes a bursary to cover the fees rate, plus an
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Funded by the Dunhill Medical Trust (dunhillmedical.org.uk), we have three fully-funded (stipend at UKRI rates (£19,327 per annum), PhD fees (for UK nationals only) and research costs) three-year
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expected to start within 2023 (but can be flexible). The successful applicant will be able to work within a vibrant and multidisciplinary aerospace team under the College of Engineering and Physical Sciences
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Supervisors: Supervisors: Dr. Albert Bartok-Partay (Physics), Prof. James Kermode (Engineering), Dr Livia Bartok-Partay (Chemistry) Summary: In high-performance applications such as aerospace and
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The team of Dr Hunt, Dr Nolan, Prof Norris, and Dr Bailey at Brunel University London is offering a fully funded PhD studentship to co-design a physical activity intervention for working-age adults
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The recent advent of deep learning (DL) has enabled data-driven models, paving the way for the full exploitation of rich image datasets from which physics can be learnt. Here at the University
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operation which are still poorly understood which affect the overall efficiency of the process. This project will aim at investigating: - the dynamics of the frothing agent with the forming bubble interfaces