Open Positions

Ph.D. students

Qualifications: We welcome applications from motivated students interested in advancing research at the intersection of network science, machine learning, and complex systems, with a particular focus on path learning and higher-order network models. Applicants should hold a Bachelor’s or Master’s degree in Engineering, Computer Science, Mathematics, Physics, or a closely related discipline. A strong background in graph theory, machine learning, network science, or computational modeling is highly desirable. Candidates should demonstrate proficiency in Python and experience with scientific computing or machine learning frameworks. Familiarity with graph neural networks, temporal networks, or sequential modeling is an advantage but not required. Applicants should possess strong analytical and problem-solving skills, excellent written and oral communication skills in English, and the ability to conduct both independent and collaborative research. Minimum application requirements established by Princeton University can be found ⁠here.

Application Instructions: Please submit your application through the ⁠Princeton University Graduate School application portal. Select the Civil and Environmental Engineering Ph.D. program and indicate your interest in working with Prof. Jürgen Hackl in your statement of purpose. The application deadline for Fall 2027 admission is December 21, 2026, at 11:59 p.m. EST.