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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 relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
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, sampling, inference, and machine learning. On one side, statistical approaches such as Bayesian inference play a critical role in identifying the parameters of PDEs, while on the other, newly emerging
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plants they visit and pollinate. Bayesian networks (BNs), and other probabilistic graphical models, can provide a visual representation of the underlying structure of a complex system by representing
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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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for a Postdoctoral Research Scientist position in applied mathematics and scientific computing, emphasizing inverse problems in seismology and Bayesian analysis. The position is associated with
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 22 days ago
- Population Genetics Course Description: This course introduces students to the genetic variation between and within populations. The topics include evolutionary forces, quantitative genetics, and Bayesian
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motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise
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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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Bayesian system identification in nonlinear engineering dynamics School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded Students Worldwide Prof Keith Worden