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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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environment with wide-ranging expertise spanning data-driven imaging, clinical science, molecular biology, bioinformatics, and biomedical engineering, all working together to improve atherosclerotic and
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of image analysis and machine learning with a minimum of 90 higher education credits. Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural
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Admission to Doctoral (PhD) Studies in the subject Engineering Sciences with specialization in Biomedical Engineering at the Division of Biomedical Engineering, Department of Materials Science and
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of new techniques for mass spectrometry imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and dysfunction. The research group has recently received