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for learning about models from data, 2) incorporation of expert knowledge in model building through Bayesian prior elicitation, and 3) develop new methods for identification of conflicts in different parts
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quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution
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@astro.uio.no ) and Prof. Hans Kristian Eriksen (h.k.k.eriksen@astro.uio.no ). The main goal of this position is to implement a novel Bayesian re-analysis pipeline for Planck HFI in the Commander pipeline, and
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to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves getting Bayesian type uncertainty
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conducting solid oxide cells (E) Skills & Abilities Practical experience of applying computational techniques to the modelling of microstructure in solid oxide cell technologies (e.g. FEM, Gaussian, Bayesian
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the Department of Applied Health Sciences and will support the delivery of the NIHR Research Professorship awarded to Professor Joht Singh Chandan (NIHR306365, https://fundingawards.nihr.ac.uk/award/NIHR306365