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vessels and ship systems. Knowledge Graphs based on engine propeller combinator diagrams of the same vessels. Machine learning algorithms for data clustering and regressions of ship performance and
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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a big plus: Relevant publications (and/or M.Sc. thesis) on the above-mentioned research topics Programming Microcontrollers and Interfacing Sensors Machine Learning Algorithms and Deep Neural Networks
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/ is a future-oriented research group with the main strengths and focus topics: Self-driving vehicles, driving algorithms and cyber-physical system Sensor fusion, perception and big data Cybersecurity
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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on sufficient and sufficiently clean water. However, we often lack the data to fully understand the dynamics of contaminants throughout the urban water cycle. Existing sensors for water quality monitoring do not
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description Cities depend on sufficient and sufficiently clean water. However, we often lack the data to fully understand the dynamics of contaminants throughout the urban water cycle. Existing sensors
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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-house database of experimental real-world data enabling large-scale validation of developed algorithms. Wind turbine drivetrains are critical components, and their failures can lead to significant