The job position is fundamental and applied research in the area of state estimation of stochastic dynamic systems with a special focus on fusion of sensor data. The system for data fusion can have centralized architecture, which corresponds to a single nonlinear filter, decentralized or distributed architecture. The aim is to analyze possibilities of adaptation of local nodes comprising nonlinear filters with respect to a global optimization objective. The adaptation can be concerned with parameters or structure of the local nonlinear filters. The local filters can be either simple filters such as the extended Kalman filter or the unscented filter or advanced filters such as the particle filter or the Gaussian mixture filter. The research can be focused either generally or with a special focus on special applications such as tracking or navigation.