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Ability to analyse and visualise disease surveillance and population health data; knowledge of infectious disease transmission dynamics; and competence in applied Bayesian statistical modelling. Strong
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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 the opportunity to work with
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with advanced statistical techniques (optimal Bayesian, Markov Chain-Monte Carlo, etc.) to solve the forward and inverse problems involved. Additional information about AGAGE, CS3, and MIT atmospheric chemistry
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, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming. Appointment, salary, and benefits. The appointment period is two years
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) incorporation of expert knowledge in model building through Bayesian prior elicitation, and 3) develop new methods for identification of conflicts in different parts of complex models. BioM is an
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getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied
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, exploratory analysis, and implementation of Bayesian modeling workflows for flood depth–damage function calibration and evaluation. The position will contribute to reproducible coding, documentation, and
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study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models
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used will the information-theoretic Bayesian minimum message length (MML) principle. Student cohort PhD, possibly Master’s (Minor Thesis) or Honours URLs/references Chen, Li and Gao, Jiti and Vahid
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. Proficiency in Python, MATLAB, or R. Strong quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with