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

Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch. The Robert Bosch GmbH is looking forward to your application!

Employment type: Limited Working hours: Full-Time Joblocation: Renningen 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 so 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 create a novel, computationally efficient, data-driven design protocol for lubricated components. In addition, you will dramatically accelerate the design process for complex EHL problems, enabling the development of more robust, efficient, and reliable tribological components for industrial applications. You will be at the forefront of integrating AI into classical engineering design. Last but not least you will 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 scientific and 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

Work-life balance: Flexible working in terms of time, place and working model. Health & Sports: Wide range of health and sports activities. Childcare: Intermediary service for childcare services. Employee discounts: Discounts for employees. Room for creativity: Space for creative work. In-house social counseling and care services: Social counselling and intermediary service for care services.

The recruitment contact or superior will be happy to provide information about the individual benefit plan. .