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structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply
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affect surface outcomes, benchmark against conventional techniques, and evaluate performance of the finished components. You’ll also delve into intelligent automation and machine learning to optimise
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external enrolment procedures. Selection criteria Demonstrated experience in programming and system development. Expertise in Python programming and data analysis. Experience developing Machine Learning
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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technologies, social structures, and networks. Effective C2 organisational systems are critical not only to military settings, but also to the operation of many civil domains, including emergency response
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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. Specific projects seeking applications are: Accelerating the discovery of inorganic solar-cell materials via a closed-loop, fully robotic synthesis–characterisation platform driven by multi-agent machine
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government background checks (allow for between 4 to 8 weeks) and complete any other CSIRO requirements. Selection criteria To be eligible applicants must: Have a basic understanding of machine learning
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of Melbourne. Learn more How can we help? Find a scholarship View scholarship guide FAQ Contact us
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at the University of Melbourne. Learn more How can we help? Find a scholarship View scholarship guide FAQ Contact us