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datasets is essential. Well-developed skills in machine learning approaches, clustering techniques and longitudinal modelling will also be highly regarded. We warmly invite applications for this exciting
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porphyry copper deposits. In this role, you will develop and apply machine-learning models to predict mineralisation using accessory minerals such as zircon and apatite, with a particular focus on
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interactions, and environmental stimuli, with applications in wearable technologies, intelligent sensing systems, human–machine interfaces, healthcare monitoring, and soft robotics. Key responsibilities include
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1: Augmented Working: Rethinking How Humans and Machines Interact, under the leadership of the Director of QWiDA. You will also collaborate across QWiDA’s university nodes and with academic colleagues
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discover them The Opportunity The Department of Electrical and Computer Systems Engineering at Monash University is seeking an outstanding and highly motivated Research Fellow to join its internationally