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we use quantum coherence to realize novel improved sensors? Can we protect quantum states and computations indefinitely so that large-scale quantum computations become possible? And does quantum
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interventions using AI? Join us to turn real-world sensor and app data into smarter, personalized digital solutions that support behavior change. PhD Candidate Predicting Adherence to Digital Health-Promoting
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Welcome to Maastricht University! Do you want to understand and predict how people engage with digital health interventions using AI? Join us to turn real-world sensor and app data into smarter
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Organisation Job description Project and job description Our project will make use sensing technologies (hyperspectral cameras, NIR and Raman sensors), and an edge-compute AI pipeline to sort used
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. Advanced (ambulatory) sensor technology combined with our broad knowledge of the human body as a dynamic system enables (eHealth) technology to improve prevention, diagnosis and treatment of sensory, motor
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lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future
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the development of a Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and
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lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future
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sensor-based measurement methods, calculation tools (such as the KringloopWijzer), and proven effective on-farm measures. Your qualities You are proactive and socially aware, enabling you to identify and
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of diverse, deformable textiles at cycle times below one second, while hyperspectral, NIR, Raman, and RGB sensors feed an edge-compute AI pipeline for real-time decision making that routes each item