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for spatiotemporal wound monitoring and patient-specific, timely wound treatment. Your tasks In this PhD project, you will develop sensors integrated in adaptive wound dressings. The sensors will be designed by
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temperature and humidity data in cold chains by commercial sensors, and deploy them in end-to-end virtual supply chains. This project also aims to better understand the tradeoffs related to cooling technology
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applications Multimodal data integration and prediction, including clinical, medical imaging, and sensor data (e.g. ECGs) The PhD student will have the opportunity to conduct both methodological and applied
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to muon g-2 from lattice Quantum Chromodynamics and algorithmic developments for multi-level and RG-improved simulations (research group of Urs Wenger) C.) Study of multi-hadron systems, with a focus on
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the implementation of mechanical testing combined with a variety of sensors to follow changes in the structures. You will use a range of surface analytical techniques to characterize the detected changes. You will
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, and limiting the potential benefits of automation. To address this, the project leverages advanced data sources (e.g., high-resolution position sensors, accelerometers, force and power sensors
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to cutting-edge tools, algorithms, and large, high-quality seismic datasets. Occasional fieldwork to acquire data from temporary networks, providing you with hands-on experience in the field. A competitive