PhD - Machine Learning-based Surrogate Modeling for Computationally Efficient Multiphysics Simulation

Shaping the future of engineering by redefining the boundaries between artificial intelligence and complex multiphysics simulations – that is your mission. Are you ready to make a crucial contribution to the development of groundbreaking design methods with your research? With us, you will not only create scientific knowledge but also lay the foundation for a new generation of efficient and reliable components in the industry.

• Your role will be to develop and establish the scientific foundations for a machine learning-based multiphysics framework, using surrogate models trained on validated EHL simulations.
• You will also create a novel, computationally efficient, data-driven design protocol for lubricated components.
• Furthermore, you will dramatically accelerate the design process for complex EHL problems, enabling the development of more robust, efficient, and reliable tribological components for critical industrial applications.
• You will be at the forefront of integrating AI into classical engineering design.
• Last but not least you will also become an expert in applying machine learning to complex engineering challenges, a skill set that will make you exceptionally valuable for leading roles in both industry and academia.

• Education: Master's degree in Mechanical Engineering, Computational Engineering, Applied Mathematics, Physics or comparable
• Experience and Know-how:
  • in-depth knowledge of numerical methods
  • a strong interest or background in machine learning
  • experience or knowledge in contact mechanics and elastohydrodynamic lubrication (EHL) is desirable
  • strong programming and scripting experience, preferably in Python
• Personality and Working Style: you have a high degree of motivation and scientific curiosity, work independently on complex issues, and always find your way to innovative solutions; you succeed in communicating your research results clearly and concisely and contributing constructively to a team; you organize your projects efficiently and keep an overview even with demanding schedules
• Languages: fluent in written and spoken English, good German language skills are an advantage