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Field
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with process safety and security concepts, accident modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Fluent in
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gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference techniques); giving mathematical proofs of their correctness and efficiency; building state
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and mortality registry, community-embedded settings for participatory research, and cutting-edge methodological expertise in causal inference and artificial intelligence methods for epidemiology and
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transcriptomics and single-cell RNA sequencing on patient samples • Mining and analyzing public cancer databases (TCGA, GEO, etc.) and omics data • Inferring TLS formation and maturation stages from
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the title of PhD Research Scholar. The Department of Business and Management Science is responsible for a specialisation in the NHH PhD programme. The specialisation has two tracks: Business Economics
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creative – You bring substantial knowledge of statistical (e.g. Bayesian) methods, strong analytical skills, and creativity. Programming skills – You are proficient in Python and/or Matlab. Research
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inference methods, survey design, and/or machine learning Experience with web scraping and API-based data collection Organizational and coordination skills, such as assisting in drafting terms of reference
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(written and spoken) The successful candidate is expected to move to Bergen Desired Qualifications: Experience with Stata Experience with causal inference methods, survey design, and/or machine learning
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are suitable. The aims of this project are to Review operating characteristics proposed for rare disease trials Develop novel Bayesian operating characteristics for different types of rare disease trials Apply
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers