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revolutionising the field of temporal analytics. We have refocused the field on methods that are both effective and feasible for non-trivial problems. We received a prestigious best paper award at the SDM data
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/edges or the changes in the “normal” concept over time. Once we proposed relevant methods we intend to further extend the approach to be able to detect anomalies in high dimensional settings as the
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of policy conditions. The fellowship project is based on critical theories from fields like political economy and STS, alongside qualitative methods including document analysis and ethnography. Proposals
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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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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