This project aims to improve the resilience of railway infrastructures by leveraging physics-enhanced machine learning. You will integrate state-of-the-art physics knowledge that governs infrastructure mechanics and dynamics with the big data from infrastructure monitoring systems. You will develop innovative physics-enhanced machine learning algorithms and models to address risks and uncertainties associated with the operational and environmental conditions of railway infrastructures. As part of this project, you will engage with railway infrastructure managers to validate your proposed solutions for resilience improvement.
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.
Qualifications
- A master's degree in Civil Engineering, Computer Science, Mechanical Engineering, Applied Mathematics, or a relevant domain.
- Good programming skills, preferably in Python.
- Affinity for some of the following fields is a plus: machine learning, civil infrastructures under extreme conditions and railway engineering.
€35000 - €55000 monthly