Master Thesis in Map Uncertainty in Autonomous Driving

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 GmbHis looking forward to your application!

Job Description

Are you passionate about the future of autonomous driving? We are seeking a talented and motivated individual to join our team of experts dedicated to advancing the capabilities of autonomous vehicles. In this role, you will play a crucial part in developing cutting-edge end-to-end (E2E) models that enhance the performance of autonomous driving systems, particularly in challenging environments where high-quality maps are not available.

• You will collaborate with a team of engineers and researchers to design and implement advanced E2E models for autonomous driving.
• Furthermore, you will focus on improving model performance in scenarios that rely on raw sensor inputs or low-quality maps, enabling the vehicle to infer its surroundings effectively.
• In addition, you will conduct experiments and analyze data to identify areas for improvement and optimize model accuracy and reliability.
• You will stay up-to-date with the latest advancements in autonomous driving technology and contribute innovative ideas to the team.
• Finally, you will document findings and present results in a publishable manner as well as work on open-source benchmarks and datasets.

Qualifications

• Education: Master studies in a relevant field or comparable with very good grades
• Experience and Knowledge: in implementing machine learning applications, in Python with PyTorch, TensorFlow or JAX
• Personality and Working Practice: an open-minded and reliable individual, who is eager to learn
• Languages: fluent in 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?
Andreas Look (Functional Department)
+49 172 4836191 

#LI-DNI

Summary

• Type: Full-time
• Function: Research