Contribute to the revolution of railway embankment monitoring. Railway embankments are vital for the safety, reliability, and resilience of rail transport. As these structures age and face increasing traffic loads and environmental impacts, efficient monitoring methods are essential. This PhD project aims to develop innovative techniques for assessing the health of railway embankments by integrating various monitoring technologies, enabling more frequent and data-driven asset management.

The Role

You will investigate the integration of Axle Box Acceleration (ABA), Laser Doppler Vibrometry (LDV), and Track Geometry (TG) data to enable indirect and frequent assessments of railway embankment conditions. Using data collected by the CTO monitoring train in the Netherlands, the research will explore the relationships between LDV measurements and existing indicators of track quality derived from ABA and TG data, aiming to establish robust indicators of embankment condition.

To support the interpretation of monitoring data, you will develop a physics-based train-track-embankment interaction model using finite element (FE) and/or multibody dynamics (MBD) approaches. This model will help investigate the mechanisms governing vibration responses measured by LDV and enhance the understanding of how embankment condition influences train-induced dynamic behavior.

Transfer functions linking LDV, ABA, TG, and wayside sensor measurements to embankment responses will be derived and validated using field data. These relationships will provide a framework for translating routinely collected monitoring data into actionable insights about embankment health and performance.

You will collaborate closely with railway industry partners, participate in discussions, and receive feedback on your research development and implementation. Limited teaching responsibilities are also included in the position.

As a PhD candidate, you will join the Railway Engineering Section within the Department of Engineering Structures at the Faculty of Civil Engineering and Geosciences at TU Delft. You will work closely with ProRail, the Dutch railway infrastructure manager, supporting the testing, validation, and practical implementation of your research outcomes. The supervisory team consists of Prof. Zili Li and Prof. Rolf Dollevoet.

About the Company

The Department of Engineering Structures focuses on developing resilient, smart, and sustainable infrastructures. Our aim is to meet societal demands in transportation, energy transition, and sustainable reuse. We conduct groundbreaking research and provide world-class education for undergraduate and graduate students, fostering an inclusive culture that values diverse perspectives.

Requirements

We are looking for an excellent candidate with the following qualifications:

• A master's degree in Civil, Geotechnical, Mechanical, Aerospace Engineering, Applied Mathematics/Mechanics, Computer Science, or related areas.
• Competence in railway/structural engineering, structural dynamics, vibration measurement and analysis, structural health monitoring, data science, or related fields.
• Programming skills in scientific computing environments such as Python, MATLAB, or similar.
• Experience with numerical modeling and simulation, preferably using FE and/or MBD approaches.
• Ability to collaborate effectively with academic researchers and industry partners.
• Excellent command of English, both verbal and written.

If your native language is not English and you do not hold a degree from an institution where English is the language of instruction, you must submit proof of English proficiency (TOEFL minimum score of 100 or IELTS minimum score of 7.0).

What We Offer

• A 4-year employment contract, divided into an initial 1.5-year contract with a progress assessment, followed by a 2.5-year contract.
• Salary ranging from €3059 to €3881 gross per month, increasing from the first to the fourth year, plus 8% holiday allowance and an end-of-year bonus of 8.3%.
• Enrollment in the TU Delft Graduate School with access to a supportive research environment and development opportunities.
• Assistance with relocation to the Netherlands, including social networking events and a Dual Career Programme for accompanying partners.

Application Process

Interested candidates should apply no later than 1 September 2026 by uploading the following documents:

• A detailed Curriculum Vitae.
• A one-page motivation letter.
• A one-page abstract of your MSc thesis in English.
• Copies of BSc and MSc degrees, transcripts, and/or publications.
• Proof of English language proficiency.

For more information about this vacancy, please contact Prof. Zili Li at z.li@tudelft.nl.