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systems that go beyond the state of the art by developing advanced vision sensor concepts, scalable embedded vision systems, and machine learning methods for industrial high-performance visual quality
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with clinicians, engineers, researchers, and industry partners to transform multimodal health data—including wearable and sensor data, medical images and video, speech, human movement, physiological
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Otaniemi campus as the work relies on the research tunnel, the rock mechanics laboratory, and other specialised software. Your network and team You will join the Mineral-based materials and mechanics
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conducts research in electronic systems design, sensor systems, cyber-physical systems, the Internet of Things and machine learning, and works on electronics from material and process to a finished
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an emphasis on object tracking, optical flow and sensor fusion Knowledge of rock mechanics, soil mechanics and/or landslide processes is considered beneficial Prior experience with point cloud
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satellite imagery can also be used for acoustic data analysis. Through sensor fusion, they provide advanced maritime and critical infrastructure surveillance from seabed to space, from DK to the Arctic
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design concepts for fluid batteries and develop tailored fabrications methods based on printing to realize and evaluate the concepts. The developed batteries will be integrated into wearable sensor
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Candidate position within the Marie Skłodowska-Curie Actions Doctoral Network ReDiLEEP (Using science-driven Re sponse Di versity knowledge to L everage E fficient E cosystem P reservationand
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Doctoral Candidate position within the Marie Skłodowska-Curie Actions Doctoral Network ReDiLEEP (Using science-driven Re sponse Di versity knowledge to L everage E fficient E cosystem P reservationand
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patient monitoring, and home-based treatment. Sensor technologies, wearable devices, and mobile sensing for collecting physiological, behavioral, and patient-reported health data. Health data science