The chair group of Aquatic Ecology and Water Quality Management, in collaboration with Quantitative Veterinary Epidemiology, Biometris, and the Wageningen Data Competence Center, invites applications from talented and enthusiastic scientists for a postdoc position (11-months fulltime) focusing on the development of automated early warning signals of disease outbreaks. Your main task is to develop and test innovative machine learning algorithms to enhance the anticipation of epidemiological critical transitions. You will be working with multivariate time series data derived from models representing diverse vector-borne diseases, complemented by real-world disease monitoring data. The machine learning approach will expand upon initial efforts, incorporating image-based representations of time series in conjunction with transfer learning techniques to devise highly effective classification systems. We are aware that this position is short-term and has a tight starting date. However, we are enthusiastic about advancing our work in machine learning alongside resilience indicators and early warning systems, and look forward to exploring future opportunities for continued projects collaboratively.

You need excellent machine learning skills and preferably experience in modelling (vector-borne) disease dynamics.

You will be part of the Aquatic Ecology and Water Quality Management group of Wageningen University. Within the theoretical part of the group (see https://sparcs-center.org/) we aim to catalyze novel insights in the mechanisms that govern resilience and critical transitions in complex systems ranging from the climate and ecosystems to society and the brain. You will be working closely together with Quantitative Veterinary Epidemiology on the vector-borne disease part of the position, and with the Wageningen Data Competence Centre for the machine learning part of the position.