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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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analysis, computational text and image analysis, or machine learning. Scientific outputs within the subject areas of IAS research. Fluency in English is required. Knowledge of Swedish is also desirable
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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well as the clinical activities at the Karolinska University Hospital, unique access to international expertise in machine learning, state-of-the-art imaging, diverse patient cohorts, and relevant computational
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backgrounds: Molecular biology, protein engineering, biochemistry. Optical engineering, fluorescence microscopy, image analysis: Development of microscopes and data analysis pipelines used to acquire and
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, Computers and Graphics Demonstrated 3D Computer Graphics experience Demonstrated experience with Machine Learning applications in and for Visualization/Computer Graphics Current experience from research in
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is now seeking a professor in pharmacology with a preclinical focus. The department has access to a wide range of methods, including advanced fluorescence microscopy (from single-molecule imaging
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fluorescence microscopy (from single-molecule imaging to intravital microscopy), electrophysiology, respirometry, microfluidics, organoid cultures, bioprinting, and excellent opportunities to work with various
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits