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and efficiency, and ensuring initiatives progress rather than stalling. The ideal candidate is comfortable navigating ambiguity, focuses on meaningful outcomes, takes ownership, and can influence
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: Aarhus University (DK) & INRAE (FR); keywords: optimisation, simulation, autonomous robots, GHG emissions PhD-O: Adaptive navigation for agricultural robots using database-driven insights. PhD grantors
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lawyer at approximately the 4–6-year post-admission level, with strong stakeholder engagement skills and the ability to navigate complex governance environments. About You You are a confident, adaptable
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project deliverables are met. Collaborate with the PI, Co-PIs and NTU team to design and develop a robust and scalable software system for autonomous agents navigating immersive 3D virtual environments (e.g
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frameworks for multi-UAV operations in Innovative Air Mobility (IAM) scenarios. The goal is to enable autonomous UAVs to perform mission-critical tasks even under adverse conditions, including GNSS
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reliability of autonomous Guidance, Navigation, and Control (GNC) algorithms when subjected to realistic stimuli. This research stems from the legacy of the ERC-funded EXTREMA and MUR-funded COSMICA projects
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of fully autonomous navigation systems. Main responsibilities Develop and optimize autonomous navigation algorithms for outdoor mobile robots. Integrate and fuse data from perceptual sensors (LiDAR, RGB
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adaptable object handling in complex real-world scenarios, including those involving deformable objects and uncertain conditions.. Semantic Navigation & Mapping – Designing solutions for robot navigation
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to design and develop a robust and scalable software system for autonomous agents navigating immersive 3D virtual environments (e.g., Roblox, Minecraft). Implement a parallelized agent-driven framework where
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set the minimum pay determined by rank and step at appointment. See the following table for the salary scale for this position: https://www.ucop.edu/academic-personnel-programs/_files/2025-26