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Field
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- Simulación en entornos virtuales para el estudio de algoritmos de clasificación de objetos y generación de datasets ------------------ - Implementation of algorithms in embedded processing systems for train
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description AI-enabled polymer monitoring via multi-sensor intelligent non
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sensor systems Implementation of digital signal processing (Python or MATLAB) Experimental characterization of optical and electrical components (lasers, optics, optical fibers, etc.) Planning, simulation
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Student assistant (m/f/d)-Multi-Modal Sensor Fusion, Object Detection in Clutter and Object Tracking
an automated evaluation pipeline. Calibrate and time-synchronize multi-camera systems with tactile sensors; define data schemas and ROS 2/Isaac ROS interfaces. Algorithm Implementation: Develop multi
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physiological signals associated with bruxism in real-time. The successful candidate will focus on: Developing and refining novel wearable sensors that are flexible, comfortable, and capable of capturing subtle
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algorithm development to hardware in the loop (HIL) validation, architectures for autonomous coordination through guidance, navigation and control of distributed space segments, under cooperative and non
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vehicle (AV), allowing for automated detection, prediction, mapping, and planning. During the vehicle’s operation, data is obtained through a myriad of sensors in an AV—including RADAR, LIDAR, cameras, and
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Model Based Design and Flight Testing of a Vertical Take-Off Vertical Landing Rocket (C3.5-MAC-John)
tested will have applications for landing on other planets or moons, or even propulsive landing of rocket stages on Earth. These missions require the use of novel guidance algorithms, sensors, and control
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, integrate, and validate sensors, especially but not limited to biomedical sensors for physiological monitoring. --Collect experimental data, implement algorithms and signal processing, contribute to system
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Literature Review: Survey reinforcement learning, in-hand manipulation, object grasping and multi-modal (vision, proprioception, and tactile) sensor fusion Framework Development: Cell setup in sim and real