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; decision-making; and management of natural resources. • Developing appropriate statistical algorithms for updating model parameter estimates. • Analyzing data and producing interactive graphical
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. The AMR sub-team estimates the global burden of drug-resistant and susceptible infections, including their geographic distribution and clinical impact. Both sub-teams rely on diverse data sources
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, as well as machine learning techniques. Experience to adapt existing methodology to new situations. Thorough skills in analysis and consultation. Demonstrated experience with data analysis, computer
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, or network-based, Bayesian or matrix factorization methods for multi-omics integration Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
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Interview Motivated in learning new methodologies and applying new knowledge Essential Interview Knowledge of the approximate Bayesian machine learning (e.g. MCMC) (assessed at: Application form/Interview
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software, technology, and relevant computer applications. Communication: Strong and clear written and verbal communication skills for interacting with colleagues and stakeholders. Department Specific
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campaigns including programmed screening or Bayesian optimisation. You will characterise the resulting materials, in terms of their properties and performance for an intended application. Sustainability will
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, Joshua W. and D.L. Dowe (2005). ``Minimum Message Length and Generalized Bayesian Nets with Asymmetric Languages'', Chapter 11 (pp265-294) in P. Gru:nwald, I. J. Myung and M. A. Pitt (eds.), Advances in
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modern clinical trial design, such as Bayesian Adaptive Clinical trial design or established expertise in statistical methods such as structural equation modeling, causal data analysis. Experience in
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-armed Bandits, Bayesian Optimization. Automated Model Design and Tuning: Neural Architecture Search, Hyperparameter Optimization. Computer Networking: Resource-Constrained Networking (e.g., Internet