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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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the environment, including traffic conditions, travel time, and cost. The project will define the DRL components (states, actions, rewards, policies), select and implement suitable DRL algorithms, and integrate
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, C/C++ and/or Java, etc.; experience with the implementation of specialized transport modelling software, optimization algorithms and procedures; strong ability and desire to learn new programming
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living allowance, a mobility allowance and a family allowance (if eligible)) starting November 1, 2025. Research areas: DC7: Programming models and high-level compilation for near-sensor dataflow execution
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prediction of queue dissolution by combining traffic flow theory with data from roadway and AMOD sensors, nonlinear optimization of the signal plan, cooperative control of traffic signals and AMOD vehicle
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the future of advanced air mobility through involvement in innovative drone-related projects that bridge technology, urban planning, material sciences, sensors and aviation. With the upcoming Smart Mobility
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. Such multimodal energy sources will become increasingly vital over the next decades, not only as sources of renewable energy but also for high-tech applications, such as powering unattended wireless sensors
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data Development of algorithms for infection and evaluation of infection hotspots in the plant population Coordination of the scientific interface to the project partners with regard to entomological
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tasks Further development of the sensor based on aerosol separation technique and field effect transistor Use aerosol measurement technique, electron-beam lithography and cleanroom equipmen Design of
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, on fundamental aspects of atomic spectroscopy and quantum physics, and will finally learn how to develop a commercial quantum sensor. Your role: Basic research in the theory and experiments with hot