Computer scientist for traffic area segmentation (f/m/d)
Indexed description
What Awaits You
Remote sensing, with its various sensors and platforms, is a valuable data source for traffic research. Entire cities and regions can be captured on a large scale and analyzed with respect to traffic-related questions.
The Institute for Remote Sensing Methodology regularly acquires aerial imagery using the aircraft and helicopters of the DLR research fleet, as well as institute-owned camera systems. In addition, the institute has access to high-resolution satellite imagery. To make optimal use of these sensor systems, methods and algorithms are developed for the automatic extraction of traffic objects and traffic areas.
These innovative algorithms play a role, for example, in the development of highly accurate, de-tailed maps for automated driving or in improving micro- and macroscopic traffic models. Novel deep learning algorithms achieve very promising results, which can be further improved and adapted to the respective task.
your tasks
- Further development of deep learning algorithms (AI methods) for application on high-resolution aerial and satellite data to capture traffic areas, including their functions (e.g., roads, access routes, bicycle paths, etc.)
- Development of a pre-operational software processor, including AI algorithms, for large-scale mapping of traffic areas
- Validation of results using independent datasets and accuracy assessments of the developed methods
- Collaboration with project partners to utilize the data for addressing traffic science-related questions
- Scientific publication of results and presentation at national and international conferences
- Completed academic university degree (Diploma/Master’s) in computer science, machine learning, or a comparable field of study
- Advanced programming skills in Python and experience with deep learning frameworks (especially PyTorch)
- Practical experience with state-of-the-art computer vision and deep learning models such as CNNs and transformers
- Experience in applying AI methods and optimizing performance with respect to accuracy and processing speed
- Ability to work collaboratively in an interdisciplinary team, strong problem-solving, communication, and presentation skills
- Good English skills (B2 level or higher)
- Experience working with remote sensing data and GIS software (e.g., ArcGIS, QGIS) is an advantage
If you have any questions about this position (Vacancy-ID 4830) please contact:
Dr. Stefan Auer
Tel.: +49 8153 28 1829
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