Phd Student
vor 2 Wochen
**Your Role / Thesis Topic**
**Semantic Segmentation** of point cloud data (e.g. LiDAR data) is a classic **AI problem** and as such a challenging task in itself. However, for the usage in Advanced Driver Assistance Systems (ADAS) it is not enough to have such a snapshot of the environment at a specific point in time. Instead it is required to constantly monitor the environment around the ego car. This can for example be done by using time sequences of semantic segmentation results to create an **Occupancy Grid Map** (OGM). In post-processing, **non-causal methods** can be used here that rely on information from past and future. This allows to close “holes” in the OGMs with information from other timestamps.
In this thesis, techniques shall be developed to create OGMs from semantic LiDAR segmentation results. Special emphasis shall be put on getting maximal benefit from the non-causal approach for this **multi-dimensional time series** data as well as on the treatment of dynamic objects (e.g. other traffic participants). In addition, the distinction between overdrivable objects (e.g. man hole covers) and non-overdrivable objects (e.g. lost cargo on the street) shall be investigated.
**We Offer**
- Funding for a 3-year full-time Ph.D. scholarship in cooperation with a university
- Opportunity to work on state-of-the-art machine learning solutions in a research-oriented environment
- Hands-on work with real-world data
- A strong global team of highly educated machine learning engineers to contribute and support you
**Your Profile**
- 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
**Interested?**
**Some see differences. We see perspectives that make us stronger.**
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.
**Some See Technology. We See a Way to Make Connections.**
We are one of the largest vehicle technology suppliers and our customers include the 25 largest automotive original equipment manufacturers (“OEMs”) in the world. We operate 127 major manufacturing facilities and 12 major technical centers utilizing a regional service model that enables us to efficiently and effectively serve our global customers from best cost countries. We have a presence in 46 countries and have approximately 18,900 scientists, engineers and technicians focused on developing market relevant product solutions for our customers’
Applications from severely disabled persons and persons of equal status will be given preferential consideration in the event of equal suitability.
Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.
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