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PhD Position in Causality-Aware Path Learning (Network Science and Machine Learning) Princeton University in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Dec 21, 2026
Country
United States
University
Princeton University
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About this position
PhD position available at Princeton University in causality-aware path learning, with a strong emphasis on network science and machine learning.
The position is within Prof. Dr. Jürgen Hackl’s Complex Infrastructure Systems Group in the Civil and Environmental Engineering environment. This is a research-oriented doctoral opening for candidates interested in computational methods, graph/network analysis, and data-driven learning approaches for infrastructure systems.
Eligibility highlights: a Master’s degree in computer science, engineering, mathematics, physics, or a related field; strong analytical skills; Python proficiency; and preferred experience in machine learning or network science.
Location: Princeton University, United States.
Deadline: 21 December 2026 (with a Fall 2027 start mentioned).
Interested applicants should follow the posted application route and submit materials before the deadline.
Funding details
Available
What's required
Master's degree in computer science, engineering, mathematics, physics, or a related field; strong analytical skills; proficiency in Python; experience in machine learning or network science is preferred.
How to apply
Apply now via the post's application link or portal. Review the position details and submit the required application materials before the deadline of 21 December 2026.
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Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.