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include Bayesian data analysis, nonparametric statistics, functional data analysis, spatio-temporal statistics, and machine learning/artificial intelligence. Many of our projects involve dynamic processes
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-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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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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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred
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engineering in healthcare. Minimum Education and/or Training: Master's degree in computer science, computer engineering, data science, information technology or related field required. PhD degree in data
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received by November 1, 2025. Preferred skills: Demonstrated experience in modeling and applied statistics including machine learning, Bayesian statistics, multivariate statistics, model assisted estimation
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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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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | 2 months 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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; 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