Master's Thesis Opportunity in 3D Scene Analysis

vor 4 Wochen

Renningen, Baden-Württemberg, Deutschland Bosch Vollzeit
Position Overview

As part of your master's thesis, you will engage in innovative, learning-based approaches to open-vocabulary 3D scene comprehension utilizing 3D scene graphs. Your focus will be on the progressive assembly and integration of these graphs.

You will play a vital role in enhancing 3D scene graph predictions across various domains, including:

  • Architectural design
  • Training data and loss function optimization
  • Model efficiency improvements
  • Real-world application of models

Additionally, you will assess your model using publicly available datasets, benchmark it against leading methodologies, and showcase its performance on real-world data through a suitable robotics platform.

There will also be opportunities to disseminate your findings at reputable peer-reviewed conferences.

Required Qualifications

  • Education: Enrollment in a master's program in Computer Science or a related field, with a strong emphasis on machine learning or deep learning, and a record of excellent academic performance.
  • Skills and Experience: Proficiency in Deep Learning, Computer Vision, and/or robotics, along with strong programming capabilities, particularly in Python or C++. Familiarity with Deep Learning frameworks such as PyTorch or Jax is essential.
  • Personal Attributes: A motivated and open-minded individual, eager to explore cutting-edge topics in machine learning research, robotics, and autonomous driving applications.
  • Language Proficiency: Fluent in English; knowledge of German is a plus.

Additional Information

Duration: 6 months

To qualify for this thesis, you must be enrolled at a university. Please submit your CV, academic transcripts, examination regulations, and, if applicable, a valid work and residence permit.

At Bosch, we value diversity and inclusion as core elements of our corporate culture. We encourage applications from all individuals, regardless of gender, age, disability, religion, ethnic background, or sexual identity.

For further inquiries regarding this position, please contact the Functional Department.

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