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biomaterials, development of wear-testing methods, crown-material processing, mechanical characterisation, surface characterisation, micro-CT and quantitative image analysis. An interdisciplinary and
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biomaterials, development of wear-testing methods, crown-material processing, mechanical characterisation, surface characterisation, micro-CT and quantitative image analysis. An interdisciplinary and
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applications to medical data. The project will combine theoretical work on multiparameter persistence with the design and implementation of algorithms for medical image analysis. The successful candidate will
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will be further developed by the successful candidate in collaboration with the supervisory team. Main tasks The successful candidate will: develop and evaluate image-classification workflows
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field high-speed microscopic imaging Experience with control and synchronization of high-speed imaging and lighting systems Experience with image post-processing and data extraction Personal
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of maturity, this technology requires to experiment a change of paradigm to guarantee a sustainable development for the years to come. One pathway to achieve this paradigm shift relies on the development
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surgery. However, the growing use of TAVI has also increased the need for accurate methods to assess valve disease, identify patients who will benefit from intervention, determine the optimal timing
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new computational paradigm that combines the versatility of the digital computer with the efficiency of close-to-physics computing. The group targets the full computational stack, from materials
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a new computational paradigm that combines the versatility of the digital computer with the efficiency of close-to-physics computing. The group targets the full computational stack, from materials
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31, 2026. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. The position is placed in the Digital Signal Processing and Image Analysis group (DSB