-
-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
-
mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering
-
biogeochemical responses. However, modeling these dynamics globally remains computationally challenging. To address this, our research employs advanced computational methods to simplify high-fidelity 1-D
-
, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modeling of pathogen biology or host