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Field
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, to support predictive modelling, deep phenotyping, and real-world evidence generation. Apply and refine causal inference methodologies, such as structural equation modelling and Bayesian approaches, to better
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project is to develop scalable and privacy-preserving Bayesian computational algorithms. The position is intended for two to three years, with an initial one-year appointment renewable contingent upon
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learning models, including their strengths, deficiencies, and strategies for (hyper)parameter optimization. Prior use of Bayesian optimization or other relevant active learning algorithms is preferred
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
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. Knowledge of ensemble reweighting techniques (e.g., Bayesian approaches, metainference) and the ability to assess model-to-data fit quality. Proficiency in Unix/Linux environments and solid programming skills
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the quantification of uncertainty for these models, e.g. through Bayesian techniques, sensitivity analysis or similar. You also possess: A PhD in Hydrology, Earth Sciences, Water Management or a similar
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parameter estimation using Bayesian inference, and/or the exploitation of Machine Learning (ML) based algorithms to reduce false positives caused by human generated interference signals in the observational
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high-dimensional neural data. Approaches used include neural network-based approaches, Bayesian inference, and more Assisting with the oversight of day-to-day functions of the lab and shared lab spaces
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mathematical information science approaches, such as scientific machine learning. Potential research topics include, but are not limited to: (1) Bayesian estimation of 3D velocity structure models using ocean
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(for example, R, Python, or Matlab). Experience with graph modeling, Bayesian statistics, or causal inference is a plus. The candidate will join an integrated team of computational scientists, molecular