PhD - Research on physics-inspired AI models for mechanical machining processes in industrial semiconductor manufacturing

Do you want to turn your ideas into useful and meaningful technologies? Whether in the area of Mobility Solutions, Consumer Goods, Industrial Technology or Energy and Building Technology - with us you improve the quality of life of people around the world. Welcome to Bosch. Robert Bosch GmbH is looking forward to your application!

Type of employment: Limited Working time: Full time Place of work: Renningen The future belongs to digitalization and e-mobility – and Robert Bosch GmbH is actively supporting it. As a pioneer in the development and production of semiconductor components for sensors and power electronics, we face the challenge of mastering the increasing requirements for semiconductor production. Our current research focuses on the control of complex interactions in mechanical processing processes. We strive to avoid undesirable qualitative restrictions and at the same time achieve a high economic yield. Also using data-based methods such as machine learning. However, the complexity of the mechanical processing processes with their variety of variants as well as many uncertainties and uncertainties makes a purely data-based analysis and optimization challenging. As part of the doctorate, it is therefore necessary to examine and develop three themes: Physical modelling: At the beginning of your activity, you become familiar with the tribological overall system of the mechanical processing process and deepen your knowledge in the physical modeling. Data-based modelling: To meet the challenges of data-based prediction, you will develop innovative hybrid models that combine data-based and physical modeling. These models will be used as part of a digital twin to analyze, optimize and monitor processing processes. Manufacturing testing & validation: Validation of the hybrid modeled variables using self-planned, carried out and evaluated experiments on a machine tool for the mechanical processing of semiconductor materials. In addition, you cooperate closely with experts for modelling and manufacturing processes, participate in scientific conferences and publish your results in renowned journals.

Education: excellent completed studies in Mechatronics/Machine Engineering, Mathematics, Physics, Technical Cybernetics, Systems Engineering or Computational Science and Engineering Experiences and know-how:funded mathematical and system-theoretical understanding with high abstraction capability of complex physical relationships sound knowledge of programming (especially Python, Matlab and C++ of advantage) good knowledge in the field of machine learning and willingness to work in manufacturing technology as well as material science in the context of semiconductor processing and to carry out some practical investigations Previous knowledge of data and physics based models desirable

Personality and working methods: They implement themselves in their own initiative and with new and unconventional solutions; as an open minded person it is easy for you to motivate yourself and others Enthusiasm: Interest in creating something new as part of an interdisciplinary team, strong interest in physical relationships and mechanical manufacturing processes for semiconductor components Languages: very good English and good German of advantage

Work-Life Balance: Flexible work in terms of time, location and work model. Health and Sports: Wide range of health and sports activities. Childcare: childcare services. Employee discounts: Advantages for employees. Free space for creative work: free space for creative work. Social counselling and care: Social counselling and brokerage services.

The future personnel department or the department will be happy to inform you about the individual service catalogue. .