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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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quantum sensing technologies (e.g., Rydberg atomic sensors) for wireless communications and sensing. Key Responsibilities: Develop quantum-related theories, models, and algorithms for various communications
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studies, technical specifications, modelling and system design. The work to be developed involves continuous analysis of the state of the art, the definition and specification of technical and functional
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for, and mitigating weather and hydrological extremes, as well as to develop effective decarbonization strategies. The possible role of AI ranges from predictive models of solar insolation and wind variables
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pioneering Australian research into a market-ready product for transport planning. About the opportunity Lead research and development of advanced computer vision models, multi-object tracking, and post
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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help guide and mentor graduate students and other junior team members working on the project
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. Responsibilities* Design, implement, and evaluate LiDAR-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help