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role Conduct research on data quality and long-term reliability in smart sensor systems for industrial monitoring Develop methods, models, and computational tools for sensor data validation, anomaly
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periods, they must constantly understand their surroundings to make smart decisions and complete tasks, such as moving safely without collisions or handling objects. Recent methods for robotic situational
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an optimal solution to it. Often, users specify their problem in a high-level, human-understandable formal language. This specification is first translated into a low-level specification a solver
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methods, e.g. Monte Carlo, Latin Hypercube sampling, to quantify uncertaintyIdentify influential parameters to support robust monitoring designUse two well-monitored landslides as benchmarksDevelop OED
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and evaluation of methods that leverage multimodal signals to improve the performance of multilingual models for low-resource languages, such as Luxembourgish. Particular emphasis will be placed