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. The focus is on developing AI-supported, sensor-based solutions for real-time monitoring and optimization of manufacturing processes. These solutions aim to assess process conditions during production
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Our research group focuses on the development of AI algorithms for industrial applications. The main scope of our activities is the optimization and automation of workflows and production systems
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for monitoring people’s health. You will focus on developing new solutions, electronics, algorithms and methods to assist individuals, physicians and sports coaches to effortlessly and continuously monitor health
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generation of enhancement algorithms tailored for endoscopic videos, with a focus on applications in real-time interventions. Development efforts will prioritize both enhancement quality and computational
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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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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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scientific questions or develop algorithms that perform automatically some challenging tasks. This typically involves exchanging actively with collaborators and domain experts to understand the precise
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systems. Your work will help to define the quality and features of our algorithms. Armed with your innovative spirit and project experience, you will manifest fresh ideas and novel approaches
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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