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, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 8 days ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine
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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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-technical audiences and engage in stakeholder or end-user consultation. DESIRED CHARACTERISTICS: Demonstrated experience in models of opinion dynamics, Bayesian reasoning models, natural language processing