Predicting Persistence of Environmental Pollutants

Most chemicals that are currently produced sooner or later end up in the environment, many of them in rivers and other waters. It is essential to know their fate in terms of transformations and persistence. Harmful chemicals that degrade quickly might pose no big thread to the environment, however persistent toxic compounds can have lasting negative impact. We will go beyond the prediction of specific biodegradation products as done in state-of-the-art metabolic prediction systems (such as enviPath and aim to predict reaction rates, that is how long pollutants and their metabolites persist in the environment. We will develop and train machine learning models that use data on metabolic reactions under certain environmental conditions and aim to predict reaction rates and the half-life of compounds.

Recommended skills: Basic knowledge of chemistry, machine learning, and python