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Imaging to contribute to the growth and success of our Bachelor of Science (Medical Radiation Science) program. This is an exciting opportunity to combine academic leadership, teaching excellence, and
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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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for the Australian Grains Industry (AAGI) program. The ideal candidate will be an expert in hyperspectral remote sensing with significant experience in data science for geospatial data analytics. This research project
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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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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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, 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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the potential to change the world. There are prestigious Scholarships in 2026 for outstanding researchers from around the world to conduct paradigm-shifting research based at any of Western Australia’s five
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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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of outcomes by November 2024. Scholarship Details Maximum number awarded 1 Eligible courses All applicable HDR courses. Eligibility criteria Outstanding Computer Science or Engineering student Knowledge of data