Thesis in Transfer Learning for Data-Based Control of Hydraulic Cylinders Robert-Bosch-Campus 1, 71272 Renningen, Germany Full-time Robert Bosch GmbH Company Description At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference. The Robert Bosch GmbH is looking forward to your application! Job Description At Bosch Corporate Research we focus on developing learning control systems for hydraulic cylinders to enhance advanced excavator assistance functions. During your thesis you will explore methods for transferring knowledge, data and model parameters between similar learning tasks to increase sample efficiency for new tasks. You will investigate measures to evaluate the performance of fine-tuned controllers to ensure they meet desired operational standards. Furthermore, you will develop strategies to reduce the computational load of model fine-tuning to enable real-time model adaptation during regular operation. Finally, you will create methods for online validation of model adaptations to ensure reliability and performance in dynamic environments. Qualifications Education: studies in the field of Electrical Engineering, Control Engineering, Computer Science, Mathematics or comparable Experience and Knowledge: in Data Science, Machine Learning, Non-Linear System identification Personality and Working Practice: you excel at sharing your thoughts openly, fostering clear communication with others, and working independently Languages: very good in English or German Additional Information Start: according to prior agreement Duration: 6 months Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit. You are almost finished with your Bachelor's degree and would like to gain some practical experience before embarking on your next academic adventure with a Master's degree? Then you fit in perfectly well with our PreMaster Programm! Take a look at our vacancies here. Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity. Need further information about the job? Ozan Demir (Functional Department) 49 711 811 45250 Matthias Woehrle (Functional Department) 49 711 811 92858 LI-DNI