Master Thesis in 3D Scene Representation and Understanding with 3D Scene Graphs

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

• During your master thesis, you will focus on learning-based, open-vocabulary 3D scene understanding using 3D scene graphs, specifically on the incremental construction and fusion of 3D scene graphs.
• You contribute to 3D scene graph prediction in one or more of the following areas: architecture design, training data and loss design, model efficiency or model application in a real-world environment.       
• Furthermore, you evaluate your model on open-source datasets, benchmark against state-of-the-art approaches and demonstrate its capabilities on real-world data on a suitable robotics platform. 
• Finally, you will have the opportunity to publish your results at peer-reviewed conferences.

Qualifications

• Education: Master studies in the field of Computer Science or comparable with a focus on machine learning/deep learning with very good grades
• Experience and Knowledge: in deep learning, computer vision, and/or robotics, strong programming skills, in particular Python or C++, knowledge in deep learning frameworks (PyTorch, Jax, etc.)
• Personality and Working Practice: an eager to learn and open-minded person 
• Enthusiasm: ready to dive into a topic at the forefront of machine learning research, robotics and autonomous driving applications
• Languages: fluent in English, German is an advantage

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?
Sebastian Koch (Functional Department)
+49 711 811 48856

#LI-DNI

Summary

• Type: Full-time
• Function: Research