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Council of Canada). The research will focus on applying, developing, and implementing novel statistical methods for causal inference, integrative data analysis, and machine learning with large
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research in causal representation learning, inference, and discovery; advance explainable models that enable discovery of image-based markers predictive of future disease evolution; and build fair, robust
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quantitative research, particularly methods for longitudinal analyses, causal inference, and natural experiments (e.g. difference in differences, interrupted time series) Demonstrated experience (as demonstrated
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