A PhD position is open within the Cluster of Excellence "Data-Integrated Simulation Science (SimTech)" in the Institute for Systems Theory and Automatic Control at the University of Stuttgart.
The project investigates the problem of characterizing uncertainty in control design approaches where controllers are synthesised using noisy data. In indirect data-driven control first a mathematical model of the system is identified from data and then classical model-based control strategies are employed for design; direct data-driven control methods unify these two steps by building maps from trajectories to controllers. The project aims at studying the fundamental uncertainty propagation mechanisms arising in these two approaches by leveraging mathematical tools from statistical learning theory, information theory, and system identification. The overarching goal is to determine whether, and in which scenarios, one approach is preferable to the other when robustness guarantees must be provided to guarantee safety.
The ideal candidates have: a degree in a relevant field, such as statistics, engineering cybernetics, computer science, electrical, mechanical, or aerospace engineering; a strong background in control and dynamical systems and/or machine learning subjects; curiosity to explore novel theoretical and algorithmic aspects of the topics above.
Interested candidates can apply by sending an email to andrea.iannelli@ist.uni-stuttgart.de with:
• Motivation letter describing background and research interests (1 page)
• Full transcripts of academic degrees
• CV (including 2-3 referees)
Starting date (flexible): Winter 2023.
For more information on this and related projects, visit the group homepage.
