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Alpes. Thanks to increasingly precise and sophisticated medical imaging techniques and fast-growing powerful image morphing tools, there are ways to predict the appearance of a patient's face after
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“interrupted” tests whereby the process is paused or slowed to allow information to be collected at a series of discrete time or load steps. This results in an estimated interpolation of events between capture
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Duration of study: Full time - 4 years fixed term (1y MRes + 3y PhD) Starting date: September 2024 Primary Supervisor: Prof. Ilias Tachtsidis, Department of Medical Physics and Biomedical
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experience in the areas of computer science, image processing, high performance computing, mathematics, and medicine. Dr Yanda Meng (Computer Vision, Medical Image Analysis, LLM), Prof Aline Villavicencio
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Supervisory Team: Joseph Lifton, Thomas Blumensath, Mark Mavrogordato Project description: Working closely with Rolls Royce, this PhD will establish advanced, but practical 3D X-ray imaging methods
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to pathogens including SARS-CoV-2. This PhD will help determine if MS and AD ChP pathology leads to altered TH transport that then causes chronic inflammation and neurodegeneration in MS and AD. The student will
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AI has the potential to revolutionise healthcare, providing tools for fast and reliable analysis and interpretation of medical data. For instance, many deep learning models for medical image
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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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the key information as listed prior to contacting a project supervisor to discuss your suitability for the position. Studentship Details One studentship available 36-month PhD 1st October 2024 start date
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microfluidics) and software, for the acquisition and real-time processing of WBCs. You will become an expert in several techniques and will be supervised by academics from the Faculty of Medical Sciences and the