Postdoc in Digital Twin Development for Optimising Crossing Geometry Profiles

We are seeking a motivated and talented Postdoctoral Researcher to join our team for an exciting opportunity in the field of railway infrastructure.

The successful candidate will contribute to the XCROSS project, part of an EU-funded international innovation programme involving collaboration with partners across Europe. The position focuses on the work package “Development of Advanced Digital Twin,” with emphasis on developing surrogate models, machine-learning-based prediction tools, and optimization routines for railway crossing asset management applications.

Job description

Key Responsibilities

• Develop fast surrogate models and machine-learning-based tools for wheel–rail interaction and crossing degradation prediction.
• Create optimization routines for crossing geometry profiles using 3D scan inspection data to improve maintenance and asset management strategies.
• Develop and implement numerical and data-driven tools in Python for digital twin applications and engineering workflows.
• Validate developed models and integrate them into the XCROSS digital twin framework in collaboration with project partners.

Candidates should have demonstrated experience in machine learning, surrogate modelling, optimization, and Python programming, preferably with existing developed tools or relevant project experience.

About the department

The Department of Engineering Structures focuses on the development of resilient, smart and sustainable structures and infrastructures. Research themes include modelling and design of railway systems, smart monitoring techniques, assessment methods for structures, and development of maintenance techniques. Its Macro Mechanics Laboratory facilities support full-scale testing, monitoring and modelling of structures to facilitate implementation of innovations.

The section of Railway Engineering deals with the physical assets of the railway system, including track, embankment, rolling stock and catenary, as well as the interfaces and dynamic interactions between them. Its research, innovation, development and education concern the whole life cycle of the assets, from design, construction, degradation, monitoring, maintenance to retrofit, as well as data-driven intelligent management of the assets, taking into consideration the performance of the whole railway system. The section plays a leading role in the TU Delft Rail Institute (DelftRail).

Job requirements

• A Ph.D. in Mechanical Engineering, Applied Mathematics, Computer Science, or a related field.
• Strong background in surrogate modelling, digital twin development and numerical simulation.
• Experience with FEM and/or multi-body software for dynamic simulations is preferable.
• Proficiency in programming languages such as Python, MATLAB, or similar.
• Demonstrated ability to conduct independent research and publish findings in peer-reviewed journals.
• Excellent problem-solving skills and attention to detail.
• Strong communication and teamwork abilities.
• Experience in project management is an advantage.

TU Delft (Delft University of Technology)

Delft University of Technology combines science, engineering and design, with strong activity in education, research and innovation in areas including energy, climate, mobility, health and digital society.

Faculty of Civil Engineering and Geosciences

The Faculty of Civil Engineering & Geosciences (CEG) is active in research and education in civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Research projects are conducted in close cooperation with a wide range of research institutions.

Conditions of employment

• Maximum duration of contract is 10 months with a fixed end date of 31 March 2027, as this will be the end date of the overall project. The appointment will ideally start as soon as possible after selection, taking into account the selection period and the required legal and administrative appointment procedures.