Anomaly detection is frequently encountered in quantitative research in the life sciences. Conventional machine learning methods are not fully adapted to deal with the identification nor the ranking of rare events. In this PhD track, we aim to combine machine learning methods with principles of extreme value theory, a field in statistics especially suited to build models of extremes.