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markers. Develop machine learning models capable of predicting Category 1 emergencies based on real-time audio features extracted from calls. Work iteratively with YAS researchers to test and refine
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, electrical engineering, technical medicine, or a related field. You have a solid background in biomedical signal analysis, physiology dynamic system, and machine learning technologies, and preferably have
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/ . The post offers an exciting opportunity for conducting internationally leading research on the whole spectrum of novel machine learning algorithms and practical medical imaging applications, aiming
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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knowledge of wireless communications, and signal processing. You have at least intermediary knowledge of machine learning algorithms, including federated learning, split learning, and graph neural networks
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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questions. Given the uncertainties involved in food supply chains, we prefer candidates who have a background in (stochastic) optimization methods (e.g., machine learning, stochastic dynamic programming
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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: TRR408-A7 Investigators: Prof. Dr. Ostap Okhrin, Chair of Econometrics and Statistics esp. in the Transport Sector and co-supervised by Prof. Dr. Kai Nagel, Chair of Transportation System
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dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven