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Field
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vehicle (AV), allowing for automated detection, prediction, mapping, and planning. During the vehicle’s operation, data is obtained through a myriad of sensors in an AV—including RADAR, LIDAR, cameras, and
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seminars, to collaborate across innovations areas within the centre, and to seek collaboration between the research partners within the centre. You will be part of a network of young researchers in deep
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mechanical ventilation, simulation, building automation and control, sensor network, thermal energy storage, indoor air quality, heat transfer, and building energy performance evaluation. Experience of test
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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aims to define the optimal specifications for spaceborne hyperspectral sensors to detect diseases in Australia’s key wheat and barley crops. The successful candidate will lead the development and
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reinforcement learning using degraded human feedbacks. Develop distributed localization approaches for multi-agent systems. Investigate the suitability of various sensors for robot navigation in human-sense
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experimental setups involving camera systems, IoT sensor networks, or embedded sensing platforms. Experience designing and conducting experiments in aquaculture, animal science, or environmental biology is
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segmentation approach based on optical sensors, and how this can be integrated with SAR sensors, current satellite imagery, previous observations in the area, weather parameters like wind speed and direction
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vehicle (AV), allowing for automated detection, prediction, mapping, and planning. During the vehicle’s operation, data is obtained through a myriad of sensors in an AV—including RADAR, LIDAR, cameras, and
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toxic gases emissions of various types of batteries potentially deployed in eHC through reduced scale testing. Lastly, you will also need to evaluate the various gas monitoring sensors performance in