Infectious disease outbreaks pose a threat to public health and can have disruptive effects on societies. Disease surveillance gives rise to diverse and continuously updated data streams. To draw valid conclusions from these, specialized mathematical and statistical modeling tools are necessary.

The proposed project is focused on the development of new statistical methods to analyze infectious disease data in real time. Possible topics include nowcasting, short-term forecasting and the estimation of reproductive numbers. Besides statistical prediction methods, it is planned to work on expert and crowd forecasts of disease spread as well as evaluation methods for such forecasts.

The position will be part of a DFG Emmy Noether Junior Researcher Group (“Multi-Model Nowcasting and Short-Term Forecasting of Infectious Disease Spread”). For parts of the project, collaborations with partners in the United Kingdom and the United States are intended.

The position is suitable for PhD studies. The planned PhD supervisors are Principal Investigators in the Helmholtz Information and Data Science School for Health, and we intend to associate doctoral candidates with this graduate school.