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the appropriate rank based on their education and experience. The broad criteria are noted below. Education The successful candidate must have the following degrees: A PhD or Doctorate in Medical Imaging, with a
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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Are you a computer scientist or machine-learning researcher interested in making medical-imaging AI work reliably beyond the dataset on which it was developed? We have an exciting two-year Grade 7
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inference workflows that can process DICOM-derived imaging at scale, generate structured quantitative outputs and operate within approved secure research computing environments. Link RAIDA-derived CT
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About Us The School of Biomedical Engineering and Imaging Sciences is an interdisciplinary School dedicated to the development, clinical translation and clinical application of medical imaging
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assessed at each stage of the recruitment process. To be considered for this post, you must also submit a separate online application to the ‘Biomedical Engineering and Imaging Science Research MPhil/PhD
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Medical Computer Vision Experience with Large Language Models and Generative AI Experience working with real-world EHR and imaging data Experience working with PACS and the DICOM standard Preferred
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: Essential criteria PhD qualified (or near completion) in Medical Physics/Imaging Biology/related field, or undergraduate qualification in a relevant discipline with experience equivalent to a PhD
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of Health Science and Technology, one or more PhD stipends in Unsupervised Learning for Medical Image Analysis are available for appointment from November 1, 2026, or as soon as possible thereafter
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image analysis, data processing and machine-learning-based modelling. More about the position The main purpose of the fellowship is research training leading to the successful completion of a PhD degree