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stochastic processes, Markov models, dynamical systems, quantum walks, or related mathematical approaches. Experience with computational model fitting, Bayesian inference, simulation, or formal model
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approaches to data analysis. We welcome applicants working across a variety of approaches, particularly computational and Bayesian, and with a range of data, including text, survey, and panel data. In
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Experience in one or more of the following areas is preferred: Statistical genetics Human genetics Population genetics Evolutionary genetics Bayesian statistics Machine learning Large-scale genomic data
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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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of them use these principles, e.g., RO membranes leverage polyamide films that act as a size filter. This project seeks to take some of the first steps to leverage anion recognition chemistry for chloride