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delivery drones, care robots, online health communities, AI-driven tools for communication and story-telling etc.) are being designed to overcome the current care crisis (aging population, shortage of care
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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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applications across the multi-billion dollar display industry, photonics, metamaterials, robotics, healthcare technologies etc. The mathematics of LCs is very rich and cuts across analysis, topology, mechanics
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the growing demand for Electric Vehicle (EV) batteries. Highly reconfigurable robotic cells powered by AI promise to deliver the new generation of resilient manufacturing systems. However, real
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agricultural vehicles and robots, tractor-implement automation, communication technologies for vehicles, navigation, guidance and planning, positioning systems, model-based control of mechatronic systems, drives
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A continual learning approach for robust robotic control in electric batteries assembly. This project is an exciting opportunity to undertake industrially linked research in partnership with
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with programming (Python, MATLAB), background in aerospace, computer science, robotics, or electrical engineering graduates, hands on skills in implementation of fusion/learning based techniques in
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Samford Ecological Research Facility VISER Allied facilities Advanced Robotics for Manufacturing Hub Herston Imaging Research Facility Translational Cell Imaging Queensland Translational Research Institute
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and robotics). Proficiency in Python, MATLAB, and/or C++ programming dialects (knowledge in other languages will be valued). Marine fieldwork experience with deployed platforms is an advantage. You must
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PhD Studentship available in the EPSRC Centre for Doctoral Training in Robotics and AI for Net Zero (RAINZ) This studentship is offered by the EPSRC Centre for Doctoral Training in Robotics and