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. mixed effects regression models and/or Bayesian statistics). You have experience in conducting empirical research (e.g., experimental design, stimuli selection, recruitment, participant testing, report
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regressions, Bayesian analyses). You preferably have experience supervising and/or teaching students. You preferably have knowledge of swarm robotics and/or deep learning artificial neural networks (e.g. CNN
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and/or Python. Experience in, and aptitude for, complex statistical modelling (inc. mixed effects regression models and/or Bayesian statistics). Excellent written and spoken English. Desirable (traits
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MMF/Nexus pipeline and the stochastic Bayesian Bisous method. To improve, extend and deepen the analysis to a full dynamical inventory, a major incentive for the project is the application and
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to microeconomics (individual choice, aggregate supply, and demand, equilibrium), econometrics (endogenous variables, choice modeling), statistics and probability, Bayesian modelling, machine learning, and deep