Postdoc​/Researcher in Digital Twin Development Optimising Crossing Geometry Profiles

Postdoc/ Researcher 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.

• Surrogate Model Development:
  Develop fast surrogate models and machine-learning-based tools for wheel–rail interaction and crossing degradation prediction.
• Optimization and Data Processing:
  Create optimization routines for crossing geometry profiles using 3D scan inspection data to improve maintenance and asset management strategies.
• Programming and Tool Development:
  Develop and implement numerical and data-driven tools in Python for digital twin applications and engineering workflows.
• Model Validation and Integration:
  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.

• Relevant degree in Mechanical Engineering, Applied Mathematics, Computer Science, or a related field.
• Strong background in surrogate modelling and 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.

• Maximum duration of contract is 10 months with a fixed end date of 31 March 2027.
• A job of 36‑40 hours per week.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customizable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

#EUfunded This is an EU funded project, named XCROSS with project number  within program HORIZON-ER-JU-2023-EXPLR-04.

Submit your application by 21 June 2026.