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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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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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, employees, IT infrastructure, specialized training). Second, they may require the use of quantitative models, data analysis, and algorithms, but these applications must also safeguard the data privacy and non
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based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored, and the findings of your project will be
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-on monitoring with cutting edge data-driven and physical based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored
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require the design of architectures suitable for real-life problems. Moreover, appropriate mathematical methods, algorithms, and applications are required. Simulators are a recognized method for
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transportation systems may include a fleet autonomous cars, vans, and buses. This PhD position within FlexMobility will focus on the underlaying assignment and routing algorithms for real-time operation of
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absorption/fluorescence and scattering experiments at X-ray free electron lasers. Your focus will be to derive new algorithms for interpretation of the scattering data by introducing chemical force-fields via
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within FlexMobility will focus on the underlaying assignment and routing algorithms for real-time operation of the vehicle fleet and the multi-objective design of the mixed transporation network. Our key
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evaluate BCI algorithms for decoding motor intentions Integrate BCI systems with KAIST’s advanced exoskeletons Conduct experiments with healthy subjects and stroke patients Collaborate closely with a KAIST