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environmental sensing. The incumbent will contribute to the development and deployment of real-time correction algorithms and hardware systems, leveraging GLAO technologies in collaboration with ULTIMATE-Subaru
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frameworks such as COLMAP and Open3D; Ability to develop algorithms for object detection and tracking, 3D reconstruction, and SLAM. Advanced Control and Intelligent RoboticsSolid knowledge of classical and
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distributed energy resources (DERs). Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging
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of information in their daily lives - from local news to institutional messaging and algorithmically curated feeds. We are investigating how trust forms, erodes, and gets repaired, and how technologies
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from multiple disciplines and institutions. RESPONSIBILITIES: Write code and develop novel theoretical and practical state of the art artificial intelligence/machine learning algorithms that are focused
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, interoperability, and compliance with emerging grid standards. Key Responsibilities: Design and develop control algorithms for grid-forming converters. Conduct simulation and experimental validation using real-time
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users, researchers, and developers, both internally at the University of Sydney and externally across multiple institutions publish research papers on mathematical theory and the development and analysis
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at the University of Sydney and externally across multiple institutions publish research papers on mathematical theory and the development and analysis of algorithms compile data sets relevant to research in
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge on control is highly preferred. Have experience and commitment to supervising student