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the smooth operation, maintenance and development of Curtin’s suite of Electron Microscopes (SEMs and TEMs), optical systems and EM sample preparation labs. You will deliver high-quality technical expertise
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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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developing and implementing algorithms for processing, imaging or inversion of seismic data, preferably using MATLAB and/or Python. Experience or demonstrated ability in processing and analysis of surface
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management skills. Candidates with laboratory skills and imaging are desired for this project. Must be eligible to enrol in PhD programs at Curtin. Application process Please send your CV, academic transcripts
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deep learning, imaging and data analysis would be helpful for this project. Must be eligible to enrol in PhD programs at Curtin University. Application process Please send your CV, academic transcripts
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implementation of the heuristic methods would be the hallmark of this study. Aims The proposed study aims to offer a paradigm shift in underground mine planning process through an integrated model that solves
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on the fate of black holes in our Galaxy. Objectives To gain a full picture of the black hole population in our Galaxy, we aim to combine novel theoretical simulations of black holes with data from nascent
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, the aim of this project is to develop and validate an experimental paradigm that can describe the dynamic processes underlying C2 agility and to characterise the situational factors by which C2 agility can
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vehicles capture videos or images for underwater pipes for inspection purposes. However, highly blurry or poor-quality videos can only be received under noisy environment. Therefore, developing accurate