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in more recent years, even though criticisms reportedly date back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum
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in more recent years, even though criticisms reportedly date back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum
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based on these models. Performing parameter estimation and uncertainty quantification using Bayesian inference techniques based on experimental and/or synthetic data. Investigating efficient data
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help develop personalised models. The practical element of your project will be based on, but not limited to, time series analysis, network analysis, Bayesian inference, Machine Learning, as well as
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help develop personalised models. The practical element of your project will be based on, but not limited to, time series analysis, network analysis, Bayesian inference, Machine Learning, as well as
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, oscillation, response-time, and evidence-accumulation phenomena. Implement simulation, parameter-estimation, and model-comparison methods in Python, MATLAB , R, or related computational environments
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scientific discovery, collaborative working experiences, and professional mentorship and support. The postdoctoral associate will be affiliated with the Center for Avian Population Studies (CAPS, https