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of the data used in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with
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will address the intricate challenge of enabling AI to learn continuously and collaboratively from wearable or mobile sensor data without compromising user privacy. Your efforts and collaborations with
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closely with a small, dedicated team, you will: Design and implement SLAM-based navigation algorithms for GPS-denied forest environments (45%) Develop multi-sensor integration software for LiDAR, cameras
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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | about 1 month ago
Is the Main Topic in Virtual and Augmented Reality and Physical Activity Research: A Bibliometric Analysis. Sensors (Basel). 2023 Mar 9;23(6):2987. doi: 10.3390/s23062987. PMID: 36991699; PMCID
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analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission management platforms, contributing to the deployment of smart UAV demonstrators under
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of the relationship between the characteristics of the roadside area and accident rates, in the development of new methods to support sustainable mobility and logistics, in the installation of sensors
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complementary active and passive sensors installed on both space- and airborne platforms. We rely on competences in environmental sciences, such as hydrology and hydraulics, meteorology, plant physiology, and
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be monitored with an ensemble of 1D pressure sensors and event cameras in a Particle Image Velocimetry (PIV) setting, to record the changes of large-scale velocity flow field. Event-based vision is
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will be embedded in the ResiRob consortium (which brings together mechanical design, embedded sensors, control, materials science) and will work in close collaboration with teams specializing in
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. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process management. Addressing data sparsity and data quality issues in industrial process data