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sensor data, including LIDAR and camera inputs, for robotics and automation applications. Conduct outdoor vehicle trials for testing and validation of perception, navigation algorithms, and self-driving
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Investigator (PI), Collaborator and the research team members to ensure all project deliverables are met. Undertake these responsibilities in the project: Develop and deploy multimodal AI algorithms for fire
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. Key Responsibilities: Develop and implement perception and control algorithms for robotic arms and embodied AI systems. Assist in integrating multimodal AI models (vision, language, force sensors) with
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identification through lab-scale and field experiments. Key Responsibilities: Develop algorithms for guided-wave analysis, response analysis, sensor fusion, and system identification using distributed and multi
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, including BIM-based SLAM, traversability map analysis, and 3D LiDAR/vision sensor fusion. • Design few-shot learning algorithms for robust detection of temporary construction objects and obstacles
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and propulsion systems. You will be part of a multidisciplinary research team to develop advanced predictive maintenance solutions involving sensor integration, high-speed data acquisition, electrical
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fusion of sensor data and energy harvesting output, enabling adaptive and energy-aware data acquisition from textile-based wearable systems. Build adaptive algorithms that dynamically optimise data
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. Key Responsibilities: Develop and implement perception and control algorithms for robotic arms and embodied AI systems. Assist in integrating multimodal AI models (vision, language, force sensors) with
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. Key Responsibilities: Develop and implement perception and control algorithms for robotic arms and embodied AI systems. Assist in integrating multimodal AI models (vision, language, force sensors) with
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fields (e.g. interpolation, climatological fill, ML-based gap-filling). • Apply noise-removal algorithms (e.g. signal filtering, radar clutter suppression, spike detection) across sensor and remote