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Although deep learning has produces state of the art results on many problems, it is a data hungry technology requiring a lot of human supervision in the form of annotated data. Potential PhD topic
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in nature, we seek to rapidly translate our research into real-world solutions to significant threats to community safety. PhD students will not directly handle this data as, in many cases, it is
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to achieve a useful digital twin); and instructional design (effective interactive visualisation and information overlay techniques to guide/instruct the user). The scope of the PhD will be narrowed
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the biological experiments are conducted. The intended departure point for this PhD project is to use reinforcement learning, a mainstream AI technique, to model task allocation mechanisms. #sustainability
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. I am seeking PhD students who are interested in taking inter-disciplinary approaches to exploring the issues above. Example questions to investigate are as follows: How do students make sense
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. Expected outcomes: The student will learn inference and representation learning methods for network data. The knowledge can be easily used to analyse other networks, including but not limited to social
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Council and in partnership with the Australian Energy Market Operator (AEMO) . This prestigious scholarship opportunity for PhD or masters by research studies at a Monash campus in Australia will empower
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Monash University-China Scholarship Council (CSC) Joint Scholarship This joint scholarship program seeks to attract high-achieving Chinese students to undertake their PhD at a Monash campus in
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computational methods for modelling social dilemmas that can account for real-world complexity in agents’ behaviour. We will build on novel computational techniques to produce realistic enough models that can be
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the simple equation that more training data = better performance. Learning—in particular, the advanced deep learning methods, like BERT for NLP and ResNet for image processing—often require thousands