Probabilistic Graphical Models are a thriving research area at the interface of probability theory and graph theory. Thanks to their modularity and expressive power, they are becoming a unifying language for the formulation of complex models. On the one hand, such models raise deep questions in statistics and optimization. At the same time, they allow to address challenging applications of image analysis in computer vision, the life sciences, earth sciences and industry.
The Research Training Group (RTG 1653) funded by the German Science Foundation (DFG) and associated with the Interdisciplinary Center for Scientific Computing (IWR) of the University of Heidelberg, Germany is now inviting applications for its third and last generation of PhD students (2016-2019).
We offer 12 Doctoral Positions (TV-L 13) for fascinating research projects on theoretical aspects and demanding and relevant applied projects.
The twelve students are expected to form a diverse and yet coherent team. All of you starting at about the same time will mean that you have a chance to learn and grow together. In addition, you may profit from some overlap with the second generation of successful RTG students and benefit from their experience and insights. The principal investigators will organize a structured teaching program that builds on your individual strengths and helps close remaining gaps to allow you to reach the forefront of research in the shortest time possible and then make your own contribution. All students will be supported both scientifically and logistically by the Heidelberg Graduate School of Mathematical and Computational Sciences. You will be jointly advised by two principal investigators from Applied Mathematics and Statistics (Petra, Schnörr, Dahlhaus, Gneiting), Computer Science (Ommer, Reinelt, Rohr), and the Heidelberg Collaboratory for Image Processing (Hamprecht, Ommer, Schnörr).
Further details:
http://academicpositions.eu