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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 19 days ago
to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig economies and prediction markets. Opportunity to supervise research students and work as part of a
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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Psychology/Cognitive Science A track record in research excellence evidenced by peer-reviewed journal articles published in high quality journals relative to opportunity Experience in cognitive psychology
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the project lead peer reviewed outputs relevant to acoustic tracking and project modelling objectives, and other objectives as appropriate. About you The University values courage and creativity; openness and
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and statistics, with expertise spanning time series analysis, Bayesian inference, financial econometrics, and data analytics. As home to one of the strongest forecasting research groups worldwide, we
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: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and
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, funding partners and collaborators Monitor and evaluate the impact of international programs against strategic objectives, ensuring alignment with global education standards and sustainable development
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an attractive remuneration and relocation package. 1. Professor, Monash Health and Climate Initiative We are seeking a distinguished academic with an outstanding track record in climate change and health
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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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efficiency. Strong analytical and numeracy skills with the ability to understand, track and communicate complex data. Excellent time management skills, with a demonstrated ability to respond to changing