Openings

Openings for Graduate Students:

We are looking for highly motivated students with strong quantitative backgrounds in at least one of the following areas: machine/deep learning, formal methods, cyber-physical systems, and are interested in one or more of the following topics: trustworthy A.I. (specific topics include neuro-symbolic reasoning, safe reinforcement learning, safe imitation learning, reward design, specification-guided learning, uncertainty quantification, and the combination of control-theoretic and learning approaches), learning-enabled cyber-physical systems, and multi-robot systems. See the Research page for more information on our current research projects.

Openings for Undergraduate Students:

We are looking for undergraduate students who are interested in building embedded systems or working with robotic platforms either in simulation or in the field.