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of avoidance in birds. The PhD will develop an aerodynamic bird collision avoidance model, combining computational fluid dynamics (CFD) of the flow around wind turbines with the aerodynamic characteristics
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an aerodynamic bird collision avoidance model, combining computational fluid dynamics (CFD) of the flow around wind turbines with the aerodynamic characteristics of flying birds to predict collision risk. This
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to operate in a scalable and decentralized manner while achieving obstacle avoidance using onboard sensing and adapting to changes in dynamic environments. In parallel to the theoretical and algorithmic
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industry and the public sector to study how intelligence emerges from the interaction between body, computation, and environment, across flying, ground, and aquatic robot configurations. Our mission is to
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innovative methods and automation into fungal research, advancing how we visualize, quantify, and interpret the hidden dynamics of mycorrhizal fungi. This enhances not only our mechanistic insights of fungal