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Field
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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collection activities. Supervision will be provided by academics from various disciplines specializing in biomechanics, image processing, and computer vision, alongside orthopaedic surgeons and academics.
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(or equivalent) in a biomedical science. Experience in neuroscience and/or immunology is desirable. Project key words Retinal imaging, data-analytics, computer vision, big data Funding The studentship, funded by
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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, biology, engineering, machine learning / data science, coding. How to apply: This is an Expression of Interest process. To express your interest in applying, candidates must supply the following information
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dosing in slowsand filters. This project suits graduates seeking careers in drinkingwater technology, sustainable infrastructure, and lowcarbon process design. Drinking-water production is under mounting
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processes that produce energy and raw materials. The Institute of Radiopharmaceutical Cancer Research develops radiotracers for imaging of cancer biomarkers and personalized therapies. In a joint effort of
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Profile: University degree (M.Sc., diploma or equivalent) in materials science, engineering sciences, or physics Experience in at least one of the methods of X-ray imaging, transmission electron microscopy
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing