About this role
<p>The Remote Sensing Technology Institute is a DLR institute with sites in Oberpfaffenhofen near Munich, Berlin-Adlershof and Neustrelitz in Mecklenburg-Western Pomerania. Together with the German Remote Sensing Data Center, the institute forms the Earth Observation Center EOC, the centre of excellence for earth observation in Germany.</p><p><strong>what awaits you</strong></p> <p>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.<br>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.<br>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.</p> <p> </p> <p><strong>your tasks</strong></p> <ul> <li>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.)</li> <li>Development of a pre-operational software processor, including AI algorithms, for large-scale mapping of traffic areas</li> <li>Validation of results using independent datasets and accuracy assessments of the developed methods</li> <li>Collaboration with project partners to utilize the data for addressing traffic science-related questions</li> <li>Scientific publication of results and presentation at national and international conferences</li> </ul> <p> </p> <p><strong>your skills</strong></p> <ul> <li>Completed academic university degree (Diploma/Master’s) in computer science, machine learning, or a comparable field of study</li> <li>Advanced programming skills in Python and experience with deep learning frameworks (especially PyTorch)</li> <li>Practical experience with state-of-the-art computer vision and deep learning models such as CNNs and transformers</li> <li>Experience in applying AI methods and optimizing performance with respect to accuracy and processing speed</li> <li>Ability to work collaboratively in an interdisciplinary team, strong problem-solving, communication, and presentation skills</li> <li>Good English skills (B2 level or higher)</li> <li>Experience working with remote sensing data and GIS software (e.g., ArcGIS, QGIS) is an advantage</li> </ul><p><span id="cke_bm_7743S" style="display:none"> </span>We look forward to getting to know you!</p> <p> </p> <p>If you have any questions about this position (<strong>Vacancy-ID <strong>4830</strong></strong>) please contact:</p> <p> </p> <p><strong><strong><strong><strong>Dr. Stefan Auer</strong></strong></strong> </strong><br>Tel.: +49 8153 28 1829 </p>