Lead of global modelling and parametric index design work on different perils

- Analysis of surrogate bedload transport data collected with acoustic sensors and accelerometers- Machine learning on time-series data to predict grain size distribution of bedload material- Uncertainty quantification of surrogate measurement processes

- Quantifying uncertainty in hydrological modelling through the use of Bayesian approaches- Parameter inference of deterministic and stochastic models based on MCMC sampling techniques- Developing conceptual models for herbicide transport in small agricultural catchments- Developing stochastic models by making parameters time-dependent- Inferring time-courses of parameters to improve models and associated predictions- Visualization of results and writing of scientific reports and publications

- Developing a spatial fish meta-population model for headwater catchments in Switzerland- Tool for supporting management decisions such as prioritizing barrier removal and restoration measures- Approximate Bayes computation for parameter inference

Geostatistical interpolation of chemical deposition in R

- Supervision of experiments in the hydraulics lab- Supporting PhD student in testing groundwater particle tracking models