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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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-throughput experiments in molecular biology, image and video analyses as well as pattern recognition of complex public health data Collaboration in the development of algorithms/methods and development
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advanced molecular and cell biological techniques, including variant screening, RNA expression analyses, immunofluorescence microscopy, and transmission electron microscopy Collecting and processing patient
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microscopy, microscopy, light sheet fluorescence microscopy) and flow cytometry is an advantage Confident handling of Microsoft Office (Excel, PowerPoint, etc.) and image processing software (e.g. ImageJ
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(https://www.cliccs.uni-hamburg.de/about-cliccs/cliccs-ll.html ). In CLICCS-M4, we are further developing the unique ICON-Coast model within the ICON Earth System Modelling Framework. The objective