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, or other relevant analytical software. • Knowledgeable of Bayesian statistical methods, numerical modeling methods, and other complex quantitative analytical methods. • Experience with open science practices
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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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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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methods, Bayesian statistics, and/or an interest in applied empirical problems. We are particularly interested in candidates with expertise in applications of artificial intelligence in marketing
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’ or ‘internationally excellent’. The highly research active SP Section comprises 13 permanent academic staff with research interests in Bayesian computational statistics and machine learning, uncertainty quantification
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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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Bayesian system identification in nonlinear engineering dynamics School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded Students Worldwide Prof Keith Worden
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 1 month 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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the team’s work across its different content areas. We are seeking a candidate with strong quantitative and statistical modeling skills, particularly in Bayesian methods, who is ready to advance their career
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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