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motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise
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experience) in epidemiology, mathematical modelling, or a closely related quantitative discipline. Strong skills in statistical inference and coding in R. Experience analysing epidemiological or infectious
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, sampling, inference, and machine learning. On one side, statistical approaches such as Bayesian inference play a critical role in identifying the parameters of PDEs, while on the other, newly emerging
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background in one of the following areas: Statistical Physics Applied Mathematics Statistics & Bayesian Inference Proficiency in Python is also expected. Contacts dbc-epi-recrutement at pasteur dot fr
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testing, propensity score methods, meta-analysis, Bayesian inference, and a wide range of regression models (linear, logistic, Poisson, negative binomial, lognormal, Cox, mixed-effects, GEE, penalized
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selection criterion in some extent. This strongly suggests revisiting the study of these latent variable models with a Bayesian point of view and to understand how this evidence lower bound integrate implicit
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polycrystalline material during plastic deformation in order to eventually predict the manner in which materials deform and fail. As a first step, we wish to infer a distribution of the directions of deformation
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in knowledge-informed machine learning. The ideal candidate will have a strong background in developing and integrating probabilistic graphical models, Bayesian networks, causal inference, Markov
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, kernel machines, decision trees and forests, neural networks, boosting and model aggregation, Bayesian inference and model selection, and variational inference. Practical and theoretical understanding
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to statistical computing, Bayesian modeling, causal inference, clinical trials and analysis of complex large-scale data such as omics data, wearable tech, and electronic health record, with specific preference