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effectively within an interdisciplinary research team. Excellent command of written and spoken English. Experience with drone-based atmospheric measurements, sensor calibration and validation, or instrument
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executed. In close collaboration with PhD researchers and project partners from TUM and ETH, you will contribute to the development of novel control and learning methods for aerial manipulators and multi
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independently while contributing effectively to collaborative research teams. Track record of supervising MSc and PhD students and participation in teaching activities. Good command of spoken and written English
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terrain, the co-evolution of morphology and control for soft and legged robots using differentiable and evolutionary optimisation, and gravity-aware locomotion strategies for mass- and energy-limited
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particular its applied mathematics and advanced numerics, as well as the team’s other main research lines (for example AI for guidance, navigation and control, unconventional computing and fundamental physics
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on agentic AI for autonomous mission planning, data acquisition and satellite tasking, adapting observation strategies based on real-time inputs and priorities. Smart Monitoring and AI-Based Control Design
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, transitions of control, driver awareness, and the communication of system capabilities and limitations. The project brings together expertise from human-computer interaction, AI, human factors, cognitive
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(for example insect-eye–inspired motion detectors for planetary landing and insect-inspired navigation algorithms) to evolutionary and neuromorphic approaches to autonomous control, as well as soft-robotic