PhD/PostDoc in Optimal Experiment Design at STU Bratislava

This project develops approaches to robust model-based design of experiments in the context of maximum-likelihood estimation. The developed approaches provide robustification of model-based methodologies for the design of optimal experiments by accounting for the effect of the parametric uncertainty. The problem of robust optimal design of experiments in the framework of nonlinear least-squares parameter estimation is well known, yet the presently existing methods do not solve it to a full extent. A promising step towards solving the problem appears to be based on multi-stage robust optimization. The multi-stage formalism can aid in identifying experiments that are better conducted in the early phase of experimentation, where parameter knowledge is poor.