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interaction and human motion analysis Prior knowledge of machine learning/deep learning applied to motion analysis (e.g., relevant courses and research experience) would be an advantage IELTS score of 6.5
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-tracking, pupillometry), cognitive modelling, and regulatory analysis to assess how algorithmic explanations shape human judgement and how existing legal and ethical frameworks align with the evolution
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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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• Strong quantitative and programming skills; experience with seismic data analysis or numerical modelling is highly desirable• Excellent written and verbal communication skills• Ability to work
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factors involved in the onset and progression of dementia. Advanced computational methods, including bioinformatics pipelines and machine learning, will be employed to uncover putative biomarkers and
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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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of cities. Develop the first national land use–transport interaction (LUTI) model for Australia. Evaluate policy scenarios involving HSR to realign population growth with sustainability goals. The selected
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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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models that can forecast the likely outcomes of current practices. The project aims to develop cutting-edge machine learning and statistical risk prediction techniques to predict each short-term, long-term
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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