PhD Operations Research and Learning Techniques

For control or scheduling problems with large instances, there is typically an obstacle that relates to the curse of dimensionality. Asymptotic analysis or intuitive heuristics can sometimes help to reach a reasonable solution, but often enough, these types of problems are too complex to be solved with traditional (probabilistic) techniques alone. The world of data analytics offers various promising techniques to deal with this issue. In this project, the PhD candidate will combine traditional techniques from applied probability and optimization with data analytical tools to come to meaningful dynamic control policies for problems that arise in (large-scale) stochastic systems/networks.

The department

The project will be carried out at the Mathematics and Computer Science department of the Eindhoven University of Technology. The department has a vibrant international environment, with 46% of the scientific staff being non-Dutch nationals and more than 100 PhD candidates. The statistics and the stochastic operations groups are part of the SPOR (Statistics, Probability Theory and Operations Research) cluster within the TU/e subdepartment Mathematics. The SPOR-cluster currently has 4 full professors, 6 part-time professors, 3 associate professors and 14 assistant professors. In addition, the cluster is strongly intertwined with EURANDOM, the European institute for research in Statistics, Probability and Stochastic Operations Research. EURANDOM is a workshop and visitor centre that exists since 1998.