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sensors capable of characterizing the dynamic state of buildings and their inhabitants. By combining multi-microphone acquisition techniques with state-of-the-art machine learning methods, acoustic sensing
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on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and Data Science, Safety and
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project topics can be found at https://indibrain.eu/recruitment . OPEN POSITION: Project 5: Modeling Individual Brain Differences using Deep Learning & Vision Neuroscience: This project sits
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-computer interfaces, audio signals for keyword spotting and artificial cochleas, and tactile signals for robot perception. Various types of bio-inspired mechanisms have been investigated in recent years
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, or roundabout navigation will be considered. In this work, we also aim to explore the use of machine learning approaches [1][2] to personalize the driving system according to individual driver preferences
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for the position. Preferred selection criteria Solid theoretical background in robot perception and navigation. Deep foundation in modern machine learning. Solid programming skills in C++ and Python. Experience with
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-of-the-art machine learning methods, acoustic sensing can provide valuable insight into a wide range of processes occurring within the built environment. Potential applications include structural health
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in English (reading, writing, speaking). • Show ability to work independently as well as in a team. • Good knowledge in AI, machine learning, data science and mathematics. • Good knowledge in one
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background and/or keen interest in spatial cognition, including topics such as spatial learning, navigation, and environmental perception and behavior. Hands-on experience in designing and using immersive
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, networking, and signal processing. You have at least intermediate knowledge of machine learning algorithms. Knowledge of satellite communications, wireless sensing, radio propagation, optimization, or digital