Master Thesis Efficient End-to-End Models for Autonomous Driving (f/m/x)

BMW M Motorsport / BMW Group; München; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A leading automotive company in Munich offers a Master's thesis position focused on autonomous driving technologies. The role includes researching advanced models, contributing to innovative AI solutions, and gaining practical experience. The ideal candidate is studying computer science, with strong skills in Python and machine learning. Flexible working hours, mentoring, and competitive remuneration are part of the offer.

Leistungen

Comprehensive mentoring & onboarding

Personal & professional development

Flexible working hours

Digital offers & mobile working

Attractive & fair remuneration

Apartment offers for students

Qualifikationen

• Studies in computer science or a related field.
• Strong knowledge in computer vision concepts.
• Excellent programming skills in Python and PyTorch.
• Motivated to support problem-solving in a team.

Aufgaben

• Research state-of-the-art autonomous driving models.
• Test and improve upon existing models.
• Contribute to implementation of novel architecture.
• Conduct experiments using advanced training infrastructure.
• Assist in presenting thesis results.

Kenntnisse

Machine learning

Artificial Intelligence

Computer vision concepts

Python programming

PyTorch

Docker

Git

Problem-solving

Team collaboration

English proficiency

Ausbildung

Computer Science or related field

Tools

Docker

Git

Jobbeschreibung

Overview

We, the BMW Group, offer you an interesting and varied Master’s thesis in the field of autonomous driving. Our team focuses on developing efficient end-to-end models to advance autonomous driving technologies. At the Autonomous Driving Campus in Unterschleißheim, you will support our research community and contribute to the development of innovative AI solutions in a dynamic and collaborative environment.

Responsibilities

• You will support researching state-of-the-art autonomous driving models and help to test and improve upon them.


• Furthermore, you will gain practical AI experience by contributing to the implementation of novel architectures or training paradigms in our research.


• In addition, you will utilize our advanced training infrastructure to conduct experiments and efficiently evaluate your approaches.


• Moreover, you will assist in presenting thesis results using the scientific method, both in written and oral formats.


• You will help to collaborate with an experienced team that publishes at international peer-reviewed conferences.


• Furthermore, you will engage with an international and diverse team of doctoral candidates and students at the Autonomous Driving Campus in Unterschleißheim.

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

Qualifications

• Studies in computer science or a related field with focus on machine learning or artificial intelligence.


• Strong knowledge in computer vision concepts, compression and pruning techniques, and state-of-the-art architectures.


• Excellent programming skills in Python and PyTorch; experience with Docker and Git is a plus.


• Motivation to support solving problems and share ideas within a team.


• Good English skills.

You are enthused by new technologies and an innovative environment? Apply now!

What do we offer?

• Comprehensive mentoring & onboarding.


• Personal & professional development.


• Flexible working hours.


• Digital offers & mobile working.


• Attractive & fair remuneration.


• Apartment offers for students (subject to availability & only Munich).


• And many other benefits - see jobs/benefits

Earliest starting date: 11/01/2025

Duration: 6 months

Working hours: Full-time

Do you have any questions? Then simply send your enquiry using our contact form. Your enquiry will then be answered by telephone or e-mail.

At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants.

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