The booming advance of artificial intelligence (AI) provides us with unprecedented opportunities in shaping our digital era. In the field of structural engineering, AI plays an important role in digital transformation concerning the whole life cycle of structures. However, one remaining challenge in AI research is the lack of interpretability, as most AI applications are driven only by data while neglecting the underlying physics. Until now, we have discovered and created knowledge for an in-depth understanding of the physics behind the functioning of engineering structures. Creating AI that can understand and utilize this knowledge is crucial for enabling better solutions for practical problems in engineering structures. Potential applications include model parameter identification, structural health monitoring, maintenance decision optimization, structural design/upgrade, and digital twins.

In this PhD project, you will explore and develop physics-informed machine learning methods for modelling the structural mechanics and dynamics of railway infrastructures. The developed methods will be rooted in state-of-the-art mathematical models of railway infrastructures, aiming to represent our existing knowledge by machine learning with global or local interpretability. As part of this project, you will engage in discussions with railway industry partners and receive feedback. Limited teaching responsibilities are also included in this position.

As a PhD student, you will be a member of the Railway Engineering section in the Department of Engineering Structures at the Faculty of Civil Engineering and Geosciences, TU Delft. You will work closely with ProRail, the Dutch railway infrastructure manager, on the validation and implementation of your research project and potential applications. The supervisor team consists of Prof. Rolf Dollevoet (promotor) and Dr. Hongrui Wang (co-promotor).

We are looking for an excellent candidate with the following qualifications, knowledge and skills:

• A master's degree in Civil Engineering, Mechanical Engineering, Applied Mathematics, Computer Science or a relavant domain.
• Demonstrated experience and knowledge in machine learning.
• Good programming skills, preferably in Python.
• Research experiences in railway engineering is a plus.
• Self-motivated, curiosity-driven, open to communicate and collaborate with peers.
• Excellent command of English, both verbally and in writing. If your mother language is not English and you do not hold a degree from an institution in which English is the language of instruction, you must submit proof of English proficiency from either TOEFL (minimum total score of 100) or IELTS (minimum total score of 7.0). Proof of English language proficiency certificates older than two years are not accepted.

Fixed-term contract: 4 Years.

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

Delft University of Technology

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Civil Engineering & Geosciences

The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource depletion, urbanisation and the availability of clean water, conducted  in close cooperation with a wide range of research institutions. CEG is convinced that Open Science helps to achieve our goals and supports its scientists in integrating Open Science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Click here to go to the website of the Faculty of Civil Engineering & Geosciences.