Internship in Deep Learning for Behavior Planning for Automated Driving
Location
Magstadt | Germany
Job description
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 internship, you will develop and refine deep learning models for behavioural planning and decision-making in autonomous vehicles.
- You will participate in the simulation and analysis of driving scenarios to understand and predict the interactions between various road users.
- You will contribute to the improvement of our AI-based planning systems, focusing on the integration of state-of-the-art deep learning techniques for real-time behaviour planning.
- Last but not least, you will collaborate with a team of experts to assess the performance of behavioural planning models in simulated and real-world environments.
Qualifications
- Education: Master studies in the field of Informatics, Electrical Engineering, Robotics, Mathematics or comparable
- Experience and Knowledge: with Deep Learning, Imitation Learning and Planning, proficient in Python, experienced with DL frameworks (preferably Pytorch)
- Personality and Working Practice: eager to learn and to push research in behavior planning for AD
- Languages: very good English
Additional Information
Start: according to prior agreement
Duration: 6 months
Requirement for this internship is the enrollment at university. Please attach your CV, transcript of records, enrollment certificate, 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?
Jürgen Mathes (Functional Department)
+49 152 08887043
#LI-DNI
Summary
- Type: Full-time
- Function: Research
Job tags
Salary