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Field
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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Overview: This exciting PhD opportunity is at the intersection of aerospace engineering and cutting-edge technology. It focuses on developing an innovative ground-based robotic inspection system
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The UCAM-SENS unit is seeking a highly motivated PhD student to join its cutting-edge research in Bioelectroanalysis. This position focuses on the development of advanced electrochemical sensing
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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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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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Qualifications Master or Honours About Swinburne University of Technology Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and
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to research this topic. Interest in laboratory work and basic technical understanding. Fluent written and spoken English. Programming skills in e.g. Python, R, Matlab and Java. Experience in image processing
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the field, from tissue scaffold design in tissue engineering evaluation to surgery. The student will focus on establishing best practice for widespread applicability, building on past skin, heart, lung, brain
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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop
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Vacancies PhD position on the pilot scale production of hollow fiber membranes and prototype dialyzers for improved dialysis therapy. Key takeaways Most patients with kidney failure receive dialysis