Stochastic Processes and Applied Statistics

The Stochastic Processes and Applied Statistics group, led by Prof. David Bolin, develops methodology for statistical models involving stochastic processes and random fields. A main focus is the development of statistical methods based on stochastic partial differential equations. This is an exciting research topic that combines methods from statistics and applied mathematics in order to construct more flexible statistical models and better computational methods for statistical inference. In parallell with the theoretical research, we work on applications in a wide range of areas, ranging from brain imaging to environmental sciences. These applications are in many cases deciding the direction of the theoretical developments, and the students in the group are typically developing methods with a specific application in mind.


We are currently looking for one postdoc and have a few open positions for PhD students.