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projects Designing for complex or high-consequence systems Human-centred product, service, or interaction design in healthcare, defence, or critical infrastructure Applied human-computer interaction or
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science, machine learning, advanced computational design, and wearable technologies. To be successful you will need: Completion of a PhD in electrical, software, optical, biomedical engineering or physics
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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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. • Drive initiatives that improve data quality, data governance, and predictive analytics capabilities • Lead the development and execution of AI and machine learning projects. • Build strong
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, machine learning, and image processing techniques Strong candidates with electrical, mechanical, and biomedical engineering backgrounds can also apply. To be eligible for this scholarship, you must: Meet
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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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or airborne plant monitoring along with their underlying physical principles. Substantial expertise in image processing particularly for multi-modal (hyperspectral, RGB, LiDAR) and high-dimensional data
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the direction of A/Prof Claudia Szabo in the School of Computer and Mathematical Sciences at the University of Adelaide. The project is a collaboration with Defence Science and Technology Group, within the Combat
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the Data and AI Centre of Excellence, delivering innovative AI solutions, enabling the development of AI across the university and delivering impactful, data-driven machine learning models across