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, mixed-effects modeling, Bayesian methods, deep learning, variational autoencoders, generative AI). Is an experienced programmer in R and/or Python, and used to working with large datasets and reproducible
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for Bayesian/statistical modelling with uncertainty analysis or programming skills in Python, MATLAB or equivalent and a background in hydraulic, kinetic or systems models. Also highly desirable to have
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criteria Machine Learning Expertise: A robust foundation in probabilistic modeling, Bayesian inference, deep learning, and/or anomaly detection Modeling & Simulation Experience: Familiarity with Building
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