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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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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
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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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, Biotechnology, Bioinformatics, Biology, Computer Science, Medical Technology, or a closely related field. Relevant experience with biomedical imaging, quantitative data analysis, image processing, machine
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26 Aug 2026 Job Information Organisation/Company Adelaide University Department Future Industries Institute Research Field Technology » Medical technology Engineering » Biomedical engineering
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will find more information about working at NTNU and the application process here. About the position We have a vacant 100% PhD position in the MRI Physics Group at the Department of Physics, NTNU
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18th October 2026 Languages English English English The Department of Physics has a vacancy for a PhD Candidate in AI-assisted medical imaging with MRI Apply for this job See advertisement Are you
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methods tailored to ILC. The PhD researcher will fine-tune and benchmark pathology foundation models using multi-site H&E and immunohistochemistry whole-slide images. The aim is to learn representations
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nearby and a very temperate climate. Qualifications Candidates should meet the following requirements: Applications must have a PhD (or foreign equivalent) in basic or clinical science, imaging physics