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learning by using Bayesian learning principles. Among other things, Bayesian learning gives AI systems the ability to quantitatively express a degree of belief about a prediction or statement. By bridging
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Indian Institute of Science Education & Research Thiruvananthapuram | Thiruvananthapuram AG s, Kerala | India | about 13 hours ago
preference for Bayesian Modeling, Bayesian Computation, Time Series Analysis, Nonparametric Statistical Methods and High-dimensional statistics. Theoretical Computer Science School of ChemistryPolymer
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Bayesian system identification in nonlinear engineering dynamics
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) for engineering systems. Our research covers surrogate modeling, reliability analysis, sensitivity analysis, optimization under uncertainty, and Bayesian calibration. We are known for developing the UQLab software
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modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian hierarchical modeling using Integrated Nested Laplace Approximation (INLA). The work will contribute to ongoing
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projects, including: The post-holder will run numerical models that simulate the dispersion of greenhouse gases through the atmosphere. These models will be used, in Bayesian inference frameworks
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international projects, including: The post-holder will run numerical models that simulate the dispersion of greenhouse gases through the atmosphere. These models will be used, in Bayesian inference frameworks
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virtual reality systems, code language models, high-level synthesis, Bayesian neural networks, and FPGA-based acceleration. To apply as a Research Associate you must have a PhD (or equivalent) in
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 23 hours 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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of Oslo. Job description A fully funded PhD position is available on the development of spatiotemporal statistical modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian