Phd Position in The Area „hybrid Machine-learning
vor 2 Wochen
**Aufgaben**:
We are committed to shape the future of automotive mobility by developing highly automated driving systems for both highway and urban areas. Our development teams in Germany and California work with state-of-the-art technologies to develop innovative and class-leading systems to provide our customers with the best experience possible. To master this challenge, we are looking for energetic and committed PhD students to conduct research within our Vehicle Intelligence Team in Stuttgart.
The focus of your PhD will be on the development of a novel, hybrid behavior and motion planning technique for autonomous vehicles, combining data-driven and model-based planning methods.
The key challenge to be addressed is the integration of a scalable machine learning based method into a model-based planner approach that can provide the required robustness and safety to deal with a wide range of complex urban scenarios.
You will be expected to make use of the latest machine learning techniques to infer the interactions of the traffic agents with each other, with the infrastructure and with the environment and integrate this information into the model-based planner approach.
This also includes the development of corresponding training strategies and evaluation metrics.
Finally, the algorithms developed should be evaluated in simulation environments, on recorded driving data and by deploying them on our test vehicles.
**Responsibilities
- Assessment of the current state-of-the-art in the area of behavior and motion planning.
- Development of behavior and motion planning algorithms using machine learning techniques in combination with classical planning techniques.
- Definition of metrics that describe the quality of a trajectory based on expert knowledge and recorded human driving data.
vImplementation of a corresponding training and evaluation concept.
- Integration of the developed methods into the AD software.
- Evaluation of the developed methods in simulation, recorded driving data and real vehicles
The requirement for hiring is the supervision of the PhD project by a university lecturer. The PhD student is responsible for choosing his/her/their own supervisor.**Qualifikationen**:
**Qualifications**:
- Excellent Master’s Degree in engineering, computer science, robotics or any related area
- Excellent programming skills in Python or C++
- Strong knowledge and in-depth understanding of machine learning techniques, especially neural networks, and the corresponding software frameworks. (e.g. pytorch or tensorflow)
- Experience with Linux and development on Linux Systems
- Fluent English skills
**Preferred Qualifications**
- Knowledge in the area of robotics and motion planning
- Basic knowledge of ADAS/AD architectures
- Excellent communication skills and desire to work as part of a global team in a multi-cultural environment
- High intrinsic motivation to perform cutting-edge research
- Highly self-organized
- Fluent proficiency in spoken and written German (optional)
**Additional information**:
Would you like to write your doctoral dissertation in cooperation with Mercedes-Benz Group AG? We offer you an international network of experts, research materials, insights into our work and a personal mentor who will serve as your contact partner in addition to your doctoral advisor at your university.
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