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Field
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microclimates that demand dense sensor networks and reliable data retrieval. This project focuses on developing nature-inspired hardware to deploy Internet of Things (IoT) sensors in forest ecosystems. Combining
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• Experience in bio-instrumentation design, specifically in integrating biological or chemical assays with electronic sensors • Experience with NFC technology • Experience developing mobile applications
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related hi-tech materials and processes, sensors and tautomeric controlled drug design, headed by Professor Liudmil Antonov. It consists 3 subdivisions, namely "Fundamental aspects of the tautomerism
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processes, sensors and tautomeric controlled drug design, headed by Professor Liudmil Antonov. It consists 3 subdivisions, namely "Fundamental aspects of the tautomerism", "Exploiting excited state
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environmental NCD risk score using statistical and ML methods. Prospective phase: Use wearable environmental and physiological sensors to track exposures and health parameters in healthy volunteers, translating
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–robot interaction and ergonomics Automation and robotised workplaces (industry use-cases) Field robotics and harsh-environment robotics Predictive maintenance, sensor systems, multimodal monitoring AI/ML
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–robot interaction and ergonomics Automation and robotised workplaces (industry use-cases) Field robotics and harsh-environment robotics Predictive maintenance, sensor systems, multimodal monitoring AI/ML
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between the simulator and sensors located in the operating room. This will require implementing data acquisition algorithms and data processing algorithms within the simulator. The second point concerns
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batteries, along with advanced sensor systems. A key focus is micro integrating energy sources and sensors into autonomous, self-powered platforms by leveraging standard silicon technologies, rapid
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programming skills (Python, MATLAB), excellent communication and ability to integrate numerical modelling, sensor technologies, and occupant-focused design. Experience in thermodynamics, building physics