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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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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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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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project management skills. Candidates with strong skillset, including familiarity with structural health monitoring, computer vision and machine learning are desired for this project. Must be eligible
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experienced supervisors, each with over 20 years of expertise in machine learning and computer vision. These supervisors have strong track records of research excellence, with numerous publications in top-tier