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. The data-driven life science initiative Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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the interface between formal verification and automated planning. This is a unique opportunity to contribute to safer, more intelligent systems through a combination of theoretical work and practical
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the mobility, ubiquity, security, and interactivity of computers, data, software, and users. The pervasive computing paradigm enables technologies such as sensors, actuators, and computers to take a back seat
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the mobility, ubiquity, security, and interactivity of computers, data, software, and users. The pervasive computing paradigm enables technologies such as sensors, actuators, and computers to take a back seat
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strongly believe a healthy work-life balance is the key to our research excellence. Please visit our website for a letter to prospective students. Project description Artificial Intelligence (AI) has
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for prevention. Today’s clinical practice often relies on subjective assessments and observations. However, advanced commercial sensor technologies combined with artificial intelligence offer new opportunities
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offers opportunities to participate in teaching and student interaction at both undergraduate and master's level. The project focuses on organic micropollutant removal from wastewater in biological
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Materials Science are found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation Product Development Material Production - and in the interaction between these areas
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rot in these trees. Studies will focus on interactions between Armillaria spp. and H. fraxineus in causing basal lesions and collar rot; the impact of site conditions (e.g. soil moisture, fertility) and
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interoperability and always-on artificial intelligence. To achieve the vision, research will focus on improving the hardware for both 6G devices and space-based satellites, developing signal processing methods