Machine Learning jobs in United States

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.

The Robert Bosch GmbH is looking forward to your application!

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.

• Education: Studies in Electrical Engineering, Control Engineering, Computer Science, Mathematics, or comparable
• Experience and Knowledge: Data Science, Machine Learning, Non-Linear System Identification
• Personality and Working Practice: You excel at sharing your thoughts openly, fostering clear communication, and working independently
• Languages: Very good in English or German

Start: According to prior agreement

Duration: 6 months

Requirement for this thesis is enrollment at university. Please attach your CV, transcript of records, examination regulations, and if indicated, a valid work and residence permit.

If you are almost finished with your Bachelor's degree and want to gain practical experience before pursuing a Master's degree, then you fit perfectly with our PreMaster Program! Check out our vacancies here.

Diversity and inclusion are core to our culture. We welcome all applications, regardless of gender, age, disability, religion, ethnic origin, or sexual identity.

Ozan Demir (Functional Department)
+49 711 811 45250

Matthias Woehrle (Functional Department)
+49 711 811 92858

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