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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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available on the development of spatiotemporal statistical modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian hierarchical modeling using Integrated Nested Laplace
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, non-parametric methods, machine learning, hierarchical Bayesian modelling, and time- and space-modelling. The group emphasizes general methodological development, often motivated by real-world
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appropriate conditions, it provides a confidence set (credibility set if prediction is Bayesian) for a multivariate estimate with statistical coverage guarantees. This PhD project aims to develop new CP methods
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); mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. More about the position The position is
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order to identify targetable molecular pathways using a range of multiomic techniques. In-depth characterization of animal models of bile duct inflammation and patients with PSC has been performed using
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are funded by the Norwegian Cancer Society as part of a project titled Targeting Mono-ADP-ribosyltransferases in Breast Cancer to Enhance Antitumor Immunity. The purpose of this project is to investigate
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, including computational and transferable skills. The DSTrain program also includes a range of cross-sectorial secondments opportunities. The target group of the program are highly talented aspiring