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September 2025. Have demonstrated experience in one of these areas: privacy-preserving technologies cybersecurity machine learning. How to apply Apply for this scholarship at the same time you apply
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are seeking a highly motivated and enthusiastic candidate with a strong interest in computer vision, AI, and robotics. The ideal candidate will have solid programming skills, particularly in Python, and be well
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(www.ledbyexperience.org) and network of collaborators in a recent review stated that societal issues of climate change, military conflict, and criminality, are inevitably connected with those of mental health and well
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reliable. This project will be supported by a robust infrastructure and an intellectually stimulating environment within our machine learning group. The PhD student will be supervised by two highly
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project management skills. Candidates with strong skillset, including familiarity with structural health monitoring, computer vision and machine learning are desired for this project. Must be eligible
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. Through application of a representative learning design framework this project will explore how representative are the training activities undertaken in different in game phase (set play / offensive
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challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up
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This research project is to understand how machine learning can be exploited in the areas of target detection and tracking. Develop tracking expertise in a new student who can subsequently work
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world, and with world-class photonic facilities at Monash. "Quantum nanophotonic chip" "Multimode imaging through ultrathin meta-optics" "Advancing optical imaging with flat optics" "Machine-learning
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with