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publications in medical image analysis or computer vision video analysis. Knowledge of ultrasound imaging is not a requirement but an interest in research at the interface of machine learning with real-world
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evaluating computational methods, analysing imaging data, collaborating with clinicians for real-world impact, and contributing to publications. About You PhD (or near completion) in computer science
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responsible for the design and testing of original machine-learning based methods for fetal heart biomarker discovery from the CAIFE image and video dataset. The full-time post is funded by InnoHK and is fixed
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processing of large data sets, knowledge of data acquisition systems, signal and image processing as well as experience in measuring acoustic pressures in cavitating liquids and high-speed filming is highly
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biochemical work with proteins and DNA will be highly rated in the selection process. The ideal candidate will have recently obtained a PhD in physics, biophysics, biochemistry, physical chemistry, engineering
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on glacier behaviour, including extreme events. For this work you should be familiar with image (pre-)processing techniques to obtain high quality quantitative data from time lapse imagery. This may include
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Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Please note that this is a PhD level
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at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have
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soft matter, with expertise in microscopy, optical imaging, and data analysis. Experience in building and working with optical traps will be highly rated in the selection process. The project also
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well as an appropriate multidisciplinary PhD Must-have background: · Strong experience in X-ray imaging, tomography or closely related 3D X-ray methods. · Experience with reconstruction, scientific coding and