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the study of the impact of digital and computational pathology on clinical workflows and patient care. Our lab is located in the heart of Munich at the TUM Klinikum rechts der Isar (MRI), Institute
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. Topic / Area: The positions are flexible in terms of research direction within 3D vision and graphics with a heavy focus on cutting-edge deep learning-based techniques. We are particularly interested in
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management. Our group combines empirical work (with experiments in the field and in the lab) and modelling techniques. The focus of this postdoctoral position is the generation of empirical datasets
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Institute (https://www.mdsi.tum.de/). The Position Plan, develop and test novel computational models for the analysis of digital pathology image data. Collaborate with pathologists and other domain experts
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the understanding of the trade-offs between production, mitigation and conservation in livestock-based systems, and to identify innovative mechanisms for landscape-level management. Our group combines empirical work
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fluids, design novel numerical simulation and optimal control schemes, and provide new means for risk management. This project mainly focuses on the analysis and optimal control of the underlying SPDE and
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assurance/quality control and data management, and provide a unique opportunity to address a broad variety of fundamental and applied ecological questions, including those related to community ecology
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the professional provision of research and patent information to science and industry as well as the development of innovative information infrastructures, e.g. with a focus on research data management, knowledge
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News Detection Topic / Area: The positions are flexible in terms of research direction within 3D vision with a heavy focus on cutting-edge deep learning-based techniques. We are particularly interested