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.