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Australian National University | Canberra, Australian Capital Territory | Australia | about 12 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 | 23 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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: 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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, 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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superannuation) Amplify your impact at a world top 50 University Join our inclusive, collaborative community Be surrounded by extraordinary ideas - and the people who discover them About Us The Department of
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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
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models to enhance the detection of online narratives. The successful candidate will be appointed to a two-year fixed-term, research-intensive position supported by ASCA’s EDT program on synthetic media and
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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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, objectives and values in action, together with relevant policies and guidelines. Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training. You should
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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