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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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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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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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100%, Zurich, fixed-term The Sensing, Interaction & Perception Lab is looking for a PhD student in Human-Computer Interaction. The project will focus on input detection from sensor signals (e.g
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+ firmware, MCU + sensor integration, ideally using nRF chips). Optional but encouraged is some experience with UWB (communication protocol, distance estimation) and basic feedback control/robotics (Kalman
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under ETH Zurich Excellent working conditions, including access to modern GPU and computing infrastructure and sensor equipment A competitive salary in accordance with the regulations of ETH Zurich Active
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addition to acquiring hands-on experience in energy storage/sensor device fabrication and testing. Consequently, students will bring multiple areas of expertise to bear in order to solve problems and will receive a