INTERNSHIP DETAILS

Thesis in Development of a Learning Based Compositional Electrical Drive Model

CompanyBosch Group
LocationRenningen
Work ModeOn Site
PostedDecember 19, 2025
Internship Information
Core Responsibilities
The goal of the thesis is to develop a compositional model for electric drives that allows for simulation, identification, and control using automatic differentiation techniques. You will conduct literature research, develop a dynamical physical electrical drive model, and implement a proof of concept for gradient-based optimization.
Internship Type
full time
Company Size
162385
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
The Bosch Group is a leading global supplier of technology and services. It employs roughly 417,900 associates worldwide (as of December 31, 2024). According to preliminary figures, the company generated sales of 90.5 billion euros in 2024. Its operations are divided into four business sectors: Mobility, Industrial Technology, Consumer Goods, and Energy and Building Technology. With its business activities, the company aims to use technology to help shape universal trends such as automation, electrification, digitalization, connectivity, and an orientation to sustainability. In this context, Bosch’s broad diversification across regions and industries strengthens its innovativeness and robustness. Bosch uses its proven expertise in sensor technology, software, and services to offer customers cross-domain solutions from a single source. It also applies its expertise in connectivity and artificial intelligence in order to develop and manufacture user-friendly, sustainable products. With technology that is “Invented for life,” Bosch wants to help improve quality of life and conserve natural resources. The Bosch Group comprises Robert Bosch GmbH and its roughly 470 subsidiary and regional companies in over 60 countries. Including sales and service partners, Bosch’s global manufacturing, engineering, and sales network covers nearly every country in the world. Bosch’s innovative strength is key to the company’s further development. At 136 locations across the globe, Bosch employs some 86,900 associates in research and development, of which nearly 48,000 are software engineers. Instagram: https://www.instagram.com/boschglobal/ Facebook: https://www.facebook.com/BoschGlobal Glassdoor: https://bit.ly/3raTZnH Imprint: www.bosch.com/corporate-information Privacy statement: https://www.bosch.com/data-protection-notice-bosch-linkedin/
About the Role

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

The identification of accurate simulation models of electric drive systems, comprising the inverter, an electric driver, and further components, is a crucial step for the design of high-performing controllers, fault diagnosis, and many other tasks. Goal of the thesis is to develop a compositional model for electric drives that allows for simulation, identification and control using automatic differentiation techniques. The main idea is to implement differentiable models for components of an electric drive that can be freely combined to an overall system model.

  • You will familiarize yourself with physical models of electric drives (electric machines, inverters, …).
  • You will do literature research on existing (ML-based) approaches for the identification of electric drives.
  • Furthermore, you will develop the dynamical physical electrical drive model combined with data-based models.
  • Last but not least, you will implement the proof of concept to demonstrate the gradient-based optimization of the overall model for a given example system under using dynamical data with ODE solvers.

Qualifications

  • Education: studies in the field of Electrical Engineering, Cybernetics, Physics, Computer Science or comparable
  • Experience and Knowledge: in Machine Learning and Python; modelling of dynamical Systems
  • Personality and Working Practice: you are flexible, enthusiastic and responsible
  • Languages: good in German and English

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.

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?
David Gänzle (Functional Department)
+49 711 811 49410

#LI-DNI

Key Skills
Electrical EngineeringCyberneticsPhysicsComputer ScienceMachine LearningPythonModellingDynamical Systems