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the area of structural health monitoring of civil engineering structures on an Australian Research Council Early Career Industry Fellowship project titled, 'Transforming Smart Bridge Monitoring by Computer
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software frameworks, algorithms, robust testing and validation methods, and/or empirically validated solutions that contribute directly to social good, promoting trust, fairness, transparency, and
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
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and it involves a large number of computational operations. A network simplification approach will be designed to slim network sizes to suit real time implementations. Robust underwater acoustic
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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optimization. -- Identify factors that contribute to the robustness of training algorithms against local minima and explore potential improvements. • Objective 4: Architectural Designs -- Evaluate the impact of
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. The organisation is currently working on research project(s) related to the release of a new digital product that conducts optimisation of AI algorithms for sustainable home retrofitting solutions. Opportunity