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: Collaborative Localization and Sensor Integration This PhD position will focus on developing and integrating methods for collaborative localization and sensor fusion in the ABBA USV system. The goal is to enable
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(Internet of Things) to global communication systems, allowing for reliable communication throughout the entire network infrastructure. The ideal candidate will thus have a strong background within global
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with Danish and international industrial partners. More information about the AI RF Sensors group is available at: https://www.es.aau.dk/research/ai-rf-sensors Qualification requirements Appointment as
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2-year postdoctoral position working on cutting-edge research in IoT sensor networks for critical infrastructure monitoring and mission-critical control systems. Expected start date and duration of
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centers on developing a framework for controlling a robotic arm equipped with a cardiac ultrasound probe and complementary sensors. The goal is to enable autonomous placement of the probe on predefined
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the development and testing of advanced control strategies for building energy systems. The work is closely connected to a real-world pilot case, where measured sensor data will be used for model calibration
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continuum robotic hardware systems Integration of miniaturized actuators and sensors into continuum robotic platforms Calibration and experimental validation of the developed robotic systems, including
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approaches for soft and continuum systems. The candidate must also demonstrate proven experience in embedded perception—covering data acquisition, signal processing, and sensor integration—and in
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offered within the Marie Skłodowska-Curie QuNEST – Quantum Enhanced Optical Communication Network Security doctoral training program (https://qunest.eu ) and the Villum Investigator Program: Power-Efficient
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estimation, and implementing sensor-based feedback control strategies. The project will also explore AI-based and reinforcement learning (RL)-based control approaches to enable intelligent and adaptive robotic