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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
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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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generation of health data scientists. Areas of expertise include bioinformatics, computational biology, artificial intelligence, network science, Bayesian methods, spatiotemporal methods, visualization
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. quantitative and/or qualitative counterfactual-based approaches, Difference in Difference models, Qualitative Comparative Analysis, Bayesian hierarchical modelling); o Experience working with and synthesizing
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. The PDRA will quantify the differences in calculated and measured experimental conditions by adapting the Geodetic Bayesian Inversion Software ( https://doi.org/10.1029/2018GC007585) ). Working alongside our
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project can be found here: https://www.imperial.ac.uk/bio-sustainable-materials/ VALUED is aiming to demonstrate the development of functional materials derived from bio-renewable resources. Several
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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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, methodologies, and information derived from Bayesian modeling, data science, cognitive science, and risk analysis. Its primary objective is to create advanced forecasting models, generate meaningful indicators
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-Doctoral Associate (9546 Post-Doctoral Associate) position. For more info on the division, visit http://www.sph.umn.edu/academics/divisions/biostatistics/. The successful candidate will work with Dr. Thierry
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valuable. Experience with population-level modeling approaches, including hierarchical or Bayesian modeling frameworks. Experience conducting research in Southeast Asia or comparable tropical field contexts