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focuses on leveraging machine learning and generative AI techniques for proactive mental health monitoring. The project comprises three primary research packages that address distinct aspects of the overall
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Bridge Monitoring by Computer Vision and Edge Computing.” PhD candidates involved in this project will be trained under the supervision of Prof. Jun Li and Dr. Zhen Peng in the emerging field of smart
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reliable. This project will be supported by a robust infrastructure and an intellectually stimulating environment within our machine learning group. The PhD student will be supervised by two highly
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autonomous robotic systems. The PhD student will be supervised by two supervisors with complementary expertise in robotics and machine learning. They have strong track records of research excellence with
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technologies will help. The school is focusing on research in AI/machine learning and signal processing which are the research areas in this proposed project. We have equipment ($30K) for collecting underwater
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skillset, including familiarity with structural health monitoring, computer vision and machine learning are desired for this project. Must be eligible to enrol in PhD programs at Curtin. Application process
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machine learning, ensuring a multidisciplinary approach to problem-solving. While traditional PDE-based methods offer a comprehensive framework, their effectiveness has been limited by computational
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Australia (BSc Data Science [Honours] Classifying Successful Patterns of Play in Field Hockey) and a Data Science PhD with the Fremantle Football Club (Sam Moffatt: Understanding Complexity: A machine
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biosignal processing, particularly EEG and NIRS, with a preferred background in rehabilitation sciences or sports science. Proficiency in data analysis and familiarity with machine learning algorithms
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(www.ledbyexperience.org) and network of collaborators in a recent review stated that societal issues of climate change, military conflict, and criminality, are inevitably connected with those of mental health and well