Job Description
Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.
The Robert Bosch GmbH is looking forward to your application!
Employment type: Limited
Working hours: Full-Time
Joblocation: Renningen
Current automated driving systems are structured in a hybrid manner, meaning that classical model-driven approaches are combined with data-driven AI approaches. So far all modules are developed or trained independently based on module-related key performance indicators. As a second step system-related evaluation is conducted in software-in-the-loop tests and closed-loop in the vehicle. The main drawbacks are on the one hand, that the independent optimization of modules offers no guarantee of a global system-related optimum and on the other hand, the manual experience-based analysis of the resulting system to determine the performance-related weak points in the architecture. The slow system design process is also a disadvantage.
- The goal of this PhD thesis is to research the system aspects of a ground breaking innovation in system design: End-2-End trainable systems.
- You will edit following research questions: How to efficiently train a system that is composed of AI sub-modules (efficient loss propagation)? How to train a hybrid system? And you will also research safety-related measures that allow introspection of the system.
- In your PhD thesis you will develop novel machine learning approaches with a focus on Video, Radar and LiDAR.
- Furthermore, you will evaluate your algorithms on public benchmark data sets and internal real-world data sets - offline as well as online.
- In addition, you will contribute to the scientific community with publications on top machine learning, system and robotics conferences as well as journals (NIPS, ICML, ICLR, CVPR, ICCV, IROS, TPAMI or IV).
- Last but not least, you will take responsibility and work in an agile as well as diverse research team with other PhD students and with a strong link to autonomous driving system research projects.
- Education: excellent degree (Master/Diploma) in Computer Science, Robotics, Electrical Engineering, Mathematics or related field
- Experience and Knowledge: profound knowledge of machine learning algorithms and principles, preferably deep learning as well as proven programming skills in Python and C++
- Personality and Working Practice: open-minded, logical thinking, goal- als well as team-oriented
- Languages: fluent in English (written and spoken), German is a plus
- Work-life balance: Flexible working in terms of time, place and working model.
- Health & Sport: Wide range of health and sports activities.
- Childcare: Intermediary service for childcare services.
- Employee discounts: Discounts for employees.
- Room for creativity: Space for creative work.
- In-house social counseling and care services: Social counselling and intermediary service for care services.
The recruitment contact or superior will be happy to provide information about the individual benefit plan.
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