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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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cardiac arrhythmia and remains challenging to treat effectively, with many patients experiencing recurrence after catheter ablation. One reason for this is the difficulty of identifying the specific
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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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at establishing synthetic motion as a new paradigm for spatio-temporal metamaterials. Collaboration within a multidisciplinary team involving experimental and theoretical physicists. Involvement in publications
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of algorithms for medical image analysis. The successful candidate will investigate computational complexity, stability, and numerical summaries of multiparameter persistence, as well as applications to medical
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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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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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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