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at UniMelb. We're committed to a barrier-free recruitment process and ongoing workplace support, providing adjustments throughout. We warmly encourage applications from people with disabilities. Learn more
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, aiding epistemic and learning processes. They fulfill evidential, didactic, and symbolic functions, and thereby produce different forms of knowledge. Relevant topics of research might consider, for example
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for Bayesian inference, inverse problems, uncertainty quantification, and scientific machine learning, with applications in environmental, scientific, and industrial imaging. The role/Te mahi We invite
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phonemic inventory is unclear. We will use ultrasound imaging of the tongue, acoustic analysis, perception experiments and free classification experiments to investigate the full inventory of NZE vowels
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Job Summary: The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on a novel urban intelligence
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: Guide junior researchers and graduate students. Required Knowledge, Skills and Abilities AI/ML Expertise: Strong knowledge of advanced machine learning, deep learning, and AI techniques. Programming
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to a major research project focused on coastal wetland sedimentology, advancing understanding of sediment processes, landscape evolution and environmental change in coastal systems. Working under broad
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sedimentology, advancing understanding of sediment processes, landscape evolution and environmental change in coastal systems. Working under broad direction, you will undertake high-quality independent and
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scalable way. This project aims to solve this by combining different kinds of data - structural, functional, and causal - into a single AI-centred computer model. We focus on the larval zebrafish, a small
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extensive knowledge of robotic navigation, machine learning or other relevant fields experience working with marine robotic systems or the data they collect, including inertial, acoustic, visual and