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to research on some of the following themes: New algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process
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at the Department of Informatics and is hosted jointly by the Network and Distributed Systems Research Group and the Robotics and Intelligent Systems Research Group. The research groups consist of around 30 full
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demand forecasting or behavior modeling Computing & Data Systems Cloud computing (AWS, Azure, GCP) Big data pipelines, distributed computing, and geospatial data processing Python, R, SQL/NoSQL
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(for example insect-eye–inspired motion detectors for planetary landing and insect-inspired navigation algorithms) to evolutionary and neuromorphic approaches to autonomous control, as well as soft-robotic
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, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. We put emphasis on methods of distributed computing, machine learning, image and text analysis