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(or equivalent) in an appropriate discipline. Ideal candidate will have some prior knowledge in deep learning and computer graphics. Subject area: Medical imaging, biomedical engineering, computer science & IT
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in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages, PyTorch Familiar with foundation models (vision large models or multi
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PhD Studentship: Experimental Investigation of Pharmaceutical Tablet Disintegration and Drug Release
should be submitted through the Chemical and Process Engineering Research PhD programme page (via the ‘Apply’ button above). In place of a research proposal, you should upload a document stating the title
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the sites to normal use. X-ray backscatter imaging is a non-destructive analysis technique, where X-rays are directed at a target and Compton/back-scattered photons imaged. Existing industrial systems with
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lives, appearing in processes such as in additive manufacturing, the Earth’s atmosphere, and inkjet/biomaterial printing. The key to understanding (and ultimately engineering) these applications is how
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, Computer Sciences or Aerospace Engineering or a related discipline; a Masters degree in these subjects would be of advantage. In addition, applicants should be able to demonstrate an interest across
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Your position Magnetic resonance imaging (MRI), developed in the early 1970s, offers exceptional soft tissue sensitivity and has powered the astounding progress of medicine over the past fifty years
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Project Link: Preclinical Evaluation of Spinal Therapies | Project Opportunities | PhD | University of Leeds Number of Positions: 1 Funding: School of Mechanical Engineering Studentship, in support
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Informatics and Image Analysis at the Department of Health Science and Technology, along with Steno Diabetes Center North Denmark. The successful candidate is expected to hold: A master’s degree in clinical
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sensors to understand their local surroundings at sea and inform optimal action. To ensure safety requires the ability to reliably detect, image and recognise their environment, in terms of surrounding sea