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Primary supervisor David Dowe Co-supervisors Michael Kamp Research area Machine Learning Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC
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Primary supervisor David Dowe Co-supervisors Michael Kamp Research area Machine Learning Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC
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Primary supervisor Aamir Cheema Research area Databases and Distributed Systems This PhD project will develop intelligent, data-driven methods for integrating diverse autonomous vehicles, such as
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Primary supervisor Aamir Cheema Research area Databases and Distributed Systems This PhD project will develop intelligent, data-driven methods for integrating diverse autonomous vehicles, such as
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Australian National University | Canberra, Australian Capital Territory | Australia | about 7 hours ago
in audiobooks, Australian publishing or reading history, or digital methods, as appropriate for their chosen topic; and Demonstrated excellent capacity and potential for research; and Fulfil the entry
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access to computing resources, conference travel support, and a structured researcher development program through the Graduate Research School. Faculty: Faculty of Arts, Society and Business Study area
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critically evaluate and extend state-of-the-art explainability methods for RL, such as policy summarization, counterfactual reasoning, and interpretable model approximations, to make robot decision
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critically evaluate and extend state-of-the-art explainability methods for RL, such as policy summarization, counterfactual reasoning, and interpretable model approximations, to make robot decision
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during cyclic injection processes using microfluidic experiments and pore-scale modelling. You will gain access to the advanced microfluidic fabrication facilities as well as high performance computing
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will focus on developing and applying novel machine learning and AI methods to improve the construction of PRS and enhance disease prediction. Students will gain experience in: Statistical genetics