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

Job Description 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. Qualifications 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