PhD Researcher in Physics-Informed Machine Learning (Traffic Modelling)

TL;DR

PhD Researcher (Physics-Informed Machine Learning): Developing next-generation hybrid traffic flow models by combining traffic theory with machine learning with an accent on Physics-Informed Neural Networks (PINNs) and data assimilation. Focus on designing physically consistent, interpretable prediction methods and validating them against large-scale real-world traffic data.

Location: Must be based in or be able to relocate to Delft, Netherlands

Salary: €3,059–€3,881 gross per month

Company

hirify.global is a leading international university of technology committed to pioneering research and education that addresses global societal challenges.

What you will do

• Develop hybrid traffic flow models integrating physical principles with machine learning.
• Investigate and implement Physics-Informed Neural Networks (PINNs) for network-wide prediction.
• Design scalable data assimilation methods for traffic state estimation and uncertainty quantification.
• Test and validate models using real-world traffic data from Dutch freeway networks.
• Collaborate with road authorities and industry partners to implement prediction methods in decision-support systems.

Requirements

• MSc degree in a STEM field.
• Strong interest in physics, complex systems, and traffic flow theory.
• Proven coding experience in Python, Matlab, Java, or C#.
• Ability to communicate complex ideas effectively.
• Must be able to work onsite in Delft, Netherlands.
• English proficiency required for academic research and thesis writing.

Culture & Benefits

• 4-year PhD position with a supportive, highly experienced research team.
• Comprehensive compensation package including 8% holiday allowance and 8.3% end-of-year bonus.
• Access to the hirify.global Graduate School and Doctoral Education Programme.
• Support for international employees including relocation assistance and a Dual Career Programme.
• Inclusive, open, and safe research environment.