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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network
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agent-based models which will then be tested against empirical data collected in diverse field sites using Approximate Bayesian Computation. The successful applicant will be supervised by the PI (Sheina
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
the structure from such data is challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine
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Review, update, and consolidate methodologies, including Bayesian methodologies, in the context of material balance evaluation Your Profile: PhD in applied mathematics, computer science, physics, or in
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statistics, in particular causal inference. You will research Bayesian causal inference for high-dimensional data, coming up with new methods and deriving theoretical results such as Bernstein-von Mises
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candidates are expected to have familiarity with cosmology, Bayesian statistical analysis, and strong software skills. CMB data analysis experience is preferred. The Johns Hopkins cosmology group offers a rich
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behavioral and/or neuroimaging experiments. (2) A strong technical background in Bayesian and reinforcement learning models. Please apply with your CV For people in the EU, click here for information on your
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closely with data scientists to interpret and predict MFA data using nonlinear reaction-diffusion models, 13C-isotopomer analysis, and MATLAB-based simulations enhanced by Bayesian Machine Learning
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chronobiology on marine animals. Experience with research on deep sea organisms Strong hands-on expertise in big data analyses, non-parametric and bayesian methods for rhythms analyses; panel models, penalized
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, particularly within the context of QMRA. Strong proficiency in R/RStudio (modeling, simulation, inferential statistics, etc.). Familiarity with Bayesian statistics. Foundational knowledge of general microbiology