Masterthesis Active Learning For Autonomous Driving Using Meta Data (F/M/X)

Key Skills

Aartificial intelligence, Analytical and Problem solving, Computer Vision (CV), Docker, Git, Metadata, Python Programming, PyTorch, TensorFlow

Job Description

World-leading technologies don’t make it into a BMW until they’ve undergone one of the most challenging journeys imaginable. It takes dynamic teams with outstanding technical skills to take them from the drawing board to the road. 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.

We, the BMW Group, offer you an interesting and varied master thesis on active learning for autonomous driving with neural networks.

Recognizing other road users and objects with a high degree of certainty is of great importance for autonomous driving. Convolutional neural networks are a promising approach in this case, offering unprecedented accuracy in the fields of semantic segmentation. However, the diversity in the scenarios which an autonomous driving system might encounter emphasizes the careful consideration of corner cases and meta information, such as daytime or weather conditions. Within this thesis, an active learning method shall be developed to provide and collect relevant data for semantic segmentation using meta information, aiming to improve task-related metrics.

What awaits you?

• Research on state-of-the-art methods in literature on active learning and semantic segmentation algorithms.
• Implementation experience by developing a new method for active learning with neural networks to efficiently detect scenes that increase the expressiveness of training data for semantic segmentation, contributing to a research code stack.
• Evaluating the success of the novel active learning method on publicly available research datasets, leveraging cutting-edge training infrastructure. 
• Engagement in a team with experience in publishing at international peer-reviewed conferences.
• Presenting the results of the thesis using the scientific method, both in written and oral form.
• Working in 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

What should you bring along? 

• You are a master student approaching the end of your degree in computer science or related fields with focus on machine learning or artificial intelligence.
• You have strong knowledge in computer vision concepts (semantic segmentation) and convolutional neural networks.
• You have very good programming skills in Python, TensorFlow and worked with modern programming environment tools such as Docker and Git.
• You speak English fluently.
• You are motivated at solving problems independently as well as sharing ideas and working in a team.

What do we offer?

• Comprehensive mentoring & onboarding.
• Personal & professional development.
• Work-Life-Balance & flexible working hours.
• Digital offers & mobile working.
• Attractive remuneration.
• Apartment offers for employees (only Munich).
• And many other benefits - see jobs/benefits

You enjoy working in an international team? Apply now!

At the BMW Group, we see diversity and inclusion in all its dimensions as a strength for our teams. Equal opportunities are a particular concern for us, and the equal treatment of applicants and employees is a fundamental principle of our corporate policy. That is why our recruiting decisions are also based on personality, experience and skills.

Find out more about diversity at the BMW Group at bmwgroup.jobs/diversity