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Field
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to academic leadership. Renowned for his work in Big Data and healthcare innovation, Dr. Madigan has authored over 200 publications covering topics such as Bayesian statistics, text mining, and probabilistic
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strengthen its actuarial science and statistics group, to support its ambitions to enhance and expand its expertise in these areas. Our staff work in various fields, such Bayesian statistics, applied
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modern clinical trial design, such as Bayesian Adaptive Clinical trial design or established expertise in statistical methods such as structural equation modeling, causal data analysis. Experience in
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be inferred from models that are incomplete and data that involve errors. For such challenges, Bayesian analysis using Markov Chain Monte Carlo (MCMC) has become the gold standard. For addressing high
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to microeconomics (individual choice, aggregate supply, and demand, equilibrium), econometrics (endogenous variables, choice modeling), statistics and probability, Bayesian modelling, machine learning, and deep
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GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI (PhD Project) Explainability and Compact representation of K-MDPs
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wild and domestic animal populations wildlife diseases and conservation network analysis of disease spread phylodynamics model-based statistical inference using Bayesian approaches vector biology
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Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. OCBE has collaborations with leading biomedical research groups in Norway and internationally. OCBE
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are required. Advanced competence in multiple approaches, such as neural ODEs, LLMs, bayesian, Lasso, large language models, and ensembling methods is required Experimental Immunologist Research Scientist
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guiding materials measurement experiments to acclerate learning the synthesis-process-structure-property relationship. Machine learning methods include, but are not limited to, Bayesian inference