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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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degree with strong skills in programming and machine learning. Please contact Zhuang Li for more information. The project focuses on developing multilingual datasets and advanced methods to detect and
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what we can learn from this to address image-based sexual violence more effectively in the contemporary media landscape; or examines the relationship between industry and regulatory institutions
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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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completed a relevant Bachelor’s Degree and Honour’s or Master’s. Desirable criteria: Practical experience and conceptual background in cellular immunology. Interest in, and ability to, learn bioinformatics
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computer vision and machine learning methods to interpret the photovoltaic (PV) solar farm's condition and perform various inspections and anomaly detection. The research will draw from state-of-art
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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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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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, audio prompts, visual overlays, physical affordances, decision trees, or conversational tools What criteria would guide your design approach? Would you prioritise ease of learning, error reduction
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@rmit.edu.au Dr. Shao, Wei (Data61, Marsfield) - wei.shao@data61.csiro.au The successful candidate is expected to have strong motivation and evidenced skills in machine learning and computer vision