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models (e.g. tumour progression, tumour-drug sensitivity, survivability) by integrating multiple and heterogeneous data with associative data mining and ensemble learning methods.
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and catalysis, with enhanced efficiencies and functionalities. This research is performed within the ARC Centre of Excellence for Future Low-Energy Electronics Technologies. As a member of my team, you
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of refereed research publications. The appointee should have advanced practical and theoretical experience in transition-metal catalysis including the ability to independently synthesise organometallic
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that deal with key challenges including: heterogeneity of IoT data, uncertainty of IoT environments, and accuracy of situation inference. Additionally, identifying situation transitions that could be
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analytics techniques to make sense of data from heterogeneous contexts. Depending on the trajectory that you take, examples of the questions that such a project could investigate include: How can multimodal
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infrastructure. We will design an AI-empowered pricing scheme considering heterogenous EV behaviours and preferences under a dynamical energy-transport environment with uncertainties. The outcomes of this project