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Euro / year + benefits). 3D Semantic Scene Understanding: The world around us exists spatially in 3D, and it is crucial to understand real-world scenes in 3D to enable virtual or robotic interactions
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interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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responsibilities: - implement, develop and extend methods for processing and analyzing single-cell RNAseq and protein profiles (CyTOF) - develop methods for second level analyses e.g. interaction networks
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