We're hiring! Princeton University's Complex Infrastructure Systems Group seeks a Ph.D. researcher in causality-aware path learning, starting Fall 2027. We will develop new machine learning methods that combine higher-order networks, graph neural networks, and sequence models to learn from paths constrained by network structure and temporal relationships. The research builds on our open-source #pathpyG library, with applications in transportation, communication, energy distribution, environmental, and societal systems.

We welcome applicants with strong Python and quantitative skills and an interest in graph machine learning. A master's degree is not required.

Application deadline: December 21, 2026, 11:59 pm EST
Apply here: https://gradschool.princeton.edu/admission-onboarding/apply