Master Thesis Machine Learning-based detection of construction sites for autonomous driving (f/m/x)

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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 in the area of Machine Learning-based detection of construction sites for autonomous driving.

Machine learning is a powerful tool to model complex mapping functions, enabling a nuanced understanding of the world and informed decision-making. In the realm of autonomous driving, we aspire to increasingly integrate machine learning systems alongside traditional approaches. This integration not only enhances perceptual capabilities but also offers the flexibility to effect minor adjustments for varied tasks without the need to revisit extensive development processes associated with classical methods. This master's thesis entails the utilization of our recorded driving data with ground truth information. The primary objective will be to leverage this data to learn an optimal mapping from input features to the detection of construction sites. To gauge the efficacy of the model, recorded test drives will serve as the benchmark.

What awaits you?

• Research on state-of-the-art methods in literature on machine learning algorithms.
• Generate a data set by collecting construction site information from recorded traces.
• Implement a robust machine learning architecture specifically designed for the detection of construction sites within the given driving scenarios.
• Train the machine learning architecture on the prepared data set and evaluate its performance against the current approaches.
• Apply the trained model on new test traces and analyse the predictions of the model.
• Presenting results through written and oral forms, employing the scientific method.
• Working in an international and diverse team at the Autonomous Driving Campus.

Please note that you must ensure that the thesis is supervised by a university.

What should you bring along?

• You are currently pursuing a master's degree in computer science or a related field, with a specialization in machine learning or artificial intelligence, and approaching the completion of your studies.
• You have strong knowledge in machine learning and deep learning.
• You have proficient programming skills in Python, with hands-on experience in PyTorch or TensorFlow. Familiarity with C++ is considered advantageous.
• You are fluent in English, enabling effective communication and collaboration within an international team. Proficiency in speaking German is a plus.
• You are motivated at solving problems independently as well as sharing ideas and working in a team.
• This master's thesis will not only involve the technical aspects of constructing and training a machine learning model but also require a nuanced understanding of how the model performs in practical, dynamic driving environments.

What do we offer?

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

You are enthused by new technologies and an innovative environment? 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
 

Earliest starting date: from 02/12/2024

Duration: 6 months

Working hours: Full-time

Contact:
BMW Group HR Team
+49 89 382-17001