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Field
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operation. Develop modular architectures for multi-agent coordination, sensing, and communication. Integrate sensor suites, flight controllers, and swarm coordination algorithms into UAV platforms. Conduct
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university/spinout environment. This is a unique opportunity to work at the forefront of applied research and innovation, helping translate novel control algorithms and hardware prototypes into real-world
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pipelines, Mixed Reality Toolkit customization, and performance tuning under hardware constraints; collaborating on robot motion planning, path optimization, and sensor data processing algorithms
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-making algorithm for autonomous vehicles. The work will involve sensor fusion, perception, trajectory prediction and test rig set-up, and experimental validation. Job Requirements: PhD Degree in Vehicle
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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metal industries. Project background Modern buildings operate thanks to a complex network of sensors and control systems at various levels, that manage tasks such as air quality control, temperature
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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National Laboratory (ORNL). The NEEM Group focuses on pushing the limitations of materials, sensors, and experiments through technology development, advanced instrumentation, irradiation experiments, and
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troubleshooting to ensure real-world readiness. Develop and implement algorithms for autonomous control, SLAM and navigation. Ensure reliable communication between hardware components and the robotic system