Master Thesis Multi-Targets Distilled End-to-End Autonomous Driving (f/m/x)

BMW Group; München; Hybrid; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A leading automotive company in Munich is offering a Master's thesis opportunity on Multi-Targets Distilled End-to-End Autonomous Driving. Candidates are expected to conduct comprehensive literature reviews, build autonomous driving models, and collaborate with experts at the Autonomous Driving Campus. Ideal candidates should be studying computer science or related fields, with strong programming skills in Python and knowledge in machine learning and autonomous systems. Flexible work arrangements available.

Leistungen

Mobile work

Student apartments (subject to availability)

Qualifikationen

• Strong understanding of Transformer-based models and attention mechanisms.
• Familiarity with modern autonomous driving architectures.
• Experience with benchmarking tools is a plus.

Aufgaben

• Conduct an in-depth literature review on end-to-end autonomous driving.
• Support building an autonomous driving model and evaluate it.
• Collaborate with software developers and machine learning engineers.

Kenntnisse

Computer science studies

Electrical engineering studies

Robotics studies

Machine learning knowledge

Deep learning knowledge

Transformer-based models understanding

Python programming

PyTorch knowledge

NumPy proficiency

English proficiency

German language skills

Ausbildung

Studies in computer science, electrical engineering, or related field

Tools

NAVSIM

Bench2Drive

nuPlan

nuScenes

CARLA

Docker

Conda

Python virtual environments

Jobbeschreibung

Advanced Driver Assistance Systems Munich 10.12.2025

Master Thesis Multi-Targets Distilled End-to-End Autonomous Driving (f/m/x)

SOME IT WORKS. SOME CHANGES WHAT'S POSSIBLE.

SHARE YOUR PASSION.

More than 90% of automotive innovations are based on electronics and software. That's why creative freedom and lateral thinking are so important in the pursuit of truly novel solutions. That’s why our experts will treat you as part of the team from day one, encourage you to bring your own ideas to the table – and give you the opportunity to really show what you can do.

Our team at the BMW Group researches and develops advanced perception and fusion strategies to drive autonomous driving technologies forward. As part of your thesis, you will support us in exploring innovative solutions for end-to-end autonomous driving with improved closed-loop performance.

What awaits you?

• You will conduct an in-depth literature review on end-to-end autonomous driving and identify research gaps.
• Furthermore, you will support building an end-to-end autonomous driving model and evaluate it on modern public benchmarks.
• In addition, you may contribute to publishing your results.
• Moreover, you will collaborate with experienced software developers and machine learning engineers at the Autonomous Driving Campus in Unterschleißheim.

Please note that your thesis must be supervised by a university on your part.

What should you bring along?

• Studies in computer science, electrical engineering, robotics or a related field with focus on machine learning, deep learning or artificial intelligence.
• Strong understanding of Transformer-based models and attention mechanisms.
• Experience with modern end-to-end autonomous driving architectures with BEV representation is a plus.
• Familiarity with NAVSIM, Bench2Drive, nuPlan, nuScenes or CARLA benchmarks is a plus.
• Proficient programming skills in Python, PyTorch and NumPy.
• Experience in configuring environments using docker, conda or python virtual environments.
• Good English skills; German is a plus.

Would you like to support us in advancing robust, efficient sensor fusion for automated driving? Then apply now!

What do we offer?

• Mobile work.
• Apartments for students (subject to availability & only at the Munich location).

Do you have questions? Then submit your inquiry easily via our contact form. Your inquiry will be answered by phone or email afterwards.

We at the BMW Group place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experiences, and skills of the applicants. More about this here.