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Australian National University | Canberra, Australian Capital Territory | Australia | about 11 hours ago
to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 15 hours 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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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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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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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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The Level A Research Fellow is responsible for advancing the University’s research objectives by contributing to a defined project in the field of applied econometrics. This position supports the development
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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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, utilise best practice research methodologies, and participate in project discussions. Actively participate with industry research partners to progress applied outcomes of fundamental research objectives
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, they will have prior knowledge of infectious disease modelling, Bayesian inference methods and optimisation methods. They will have a developing research profile, with a demonstrated ability to publish
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming