Master Thesis in Evaluation and Implementation of Machine Learning Methods for Driver Assistance and Autonomous Driving
- Full-time
- Legal Entity: Robert Bosch GmbH
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 GmbH is looking forward to your application!
Job Description
- During your master thesis, you will contribute to scientific research in the field of autonomous driving and advanced driver assistance systems.
- You will work with data from various sources in the automotive domain, i.e. extract, pre-process and enrich data, develop models and visualise results.
- Furthermore, you will conceptualize and setup processing pipelines and tools.
- In addition, you will get the chance to work with experienced software developers and be part of an agile team. Furthermore, you will have the chance to work mobile partially.
- Finally, you will contribute to something big, such as exploring the possibilities of synthetic data or anonymisation, and the exact tasks will depend on your previous experience.
Qualifications
- Education: Master studies in the field of Science, Technology, Engineering, Mathematics or comparable with good grades
- Experience and Knowledge: programming experience, especially in Python, knowledge in AI / Machine Learning, ideal knowledge in a relevant data analytics project, i.e. data collection, preparation, processing, modeling, analysis and visualization, experience in PyTorch/TensorFlow and neural networks as well as synthetic environmental generation is beneficial
- Personality and Working Practice: motived, self-organized, goal-oriented and team player
- Work Routine: partially mobile working within Germany
- Languages: fluent in German and English
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?
Jerg Pfeil (Functional Department)
+49 7062 911 8271
#LI-DNI