PhD Student (f/m/d) for Thesis Topic: HD Maps for ADAS AI
Location Wuppertal, North Rhine-Westphalia, Germany
Job ID J000632812
In more and more cars, a variety of sensors are installed for environmental perception to enable Advanced Driver Assistance Systems and Automated Driving Features. In addition to passive sensors (e.g. cameras), active sensors such as LiDAR and radar are increasingly used. Thereby every sensor comes with its strength and weaknesses. Every individual recording can only capture limited information about the environment, while many applications benefit from having a "condensed" representation over multiple recordings and sensor data about the environment.
Therefore we aim to aggregate data from multiple sources, into a unified world representation (HD Map). We investigate how a "condensed" model of the environment can be derived from the variety of sensor data that could be taken by different vehicles at different points in time. During your PhD you will develop new data processing and Machine Learning methods to derive insights from a large and ever growing body of real world recording data. Particular focus will be placed on the distinction between static objects (e.g., traffic lights) and dynamic objects (e.g., cars), as these must be treated differently.
Where the aggregation of static objects lay the foundation, the smart aggregation of dynamic objects and environments can inform a multitude of scenarios relevant to scene understanding. Behavior derived from dynamic objects as well as change detection are topics of interest in your research. The question whether a lane has become unavailable due to construction work, can thereby serve as an example for an automatically deducted scenario from available data.
Funding for a 3-year full-time Ph.D. scholarship in cooperation with a university
The opportunity to work on state-of-the-art machine learning solutions in a research-oriented environment
Hands-on work with real-world data to develop and test your machine learning solution
A strong, supportive global team of highly educated machine learning engineers to contribute and support you
You hold a master’s degree in Computer Science, Engineering or similar
You have practical experience with at least one ML framework like Tensorflow, Keras, Caffe, PyTorch, fast.ai etc
You can program self-reliant in Python and/or C++
You have good English skills (German skills would be a plus)
You are looking for a challenging task, bring a high level of self-motivation and like to be part of a team
Great! Please apply and include your CV and (important!) a grade overview.
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Diversity and Inclusion are sources of innovation and creativity, both of which are essential to Aptiv’s success. Everyday our diverse team comes together, drives innovation, pursues solutions, and meets challenges using their unique abilities, perspectives and talents, changing what tomorrow brings. When you join our team, you’ll get encouraged to think boldly, express your viewpoint and innovate as a matter of habit.
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