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Student of Natural Sciences, Engineering or Computer Science (f/m/d)
Job Description
Req ID:  5476
Place of work:  Oberpfaffenhofen
Starting date:  baldmöglichst
Career level:  Student research project and final thesis
Type of employment:  Part time, Full-time
Duration of contract:  6 Monate

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 12,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!

The Institute of Remote Sensing Methodology 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 Centre, the Institute forms the Earth Observation Centre (EOC), Germany’s centre of excellence for Earth observation. 

what to expect

This research proposes a diffusion-based generative framework for reconstructing building roof planes directly from very high–resolution (VHR) true-ortho aerial imagery. Inspired by the architectural layout synthesis paradigm of HouseDiffusion, the model instead predicts structured roof-plane configurations by conditioning the diffusion process on both image features and graph-based spatial relationships between neighboring roof elements. A roof adjacency graph encodes geometric and topological constraints (e.g., shared ridges, plane orientation continuity), enabling the model to incorporate contextual structural priors during generation. The diffusion process iteratively refines candidate roof plane representations while respecting these relational constraints. This formulation enables structured roof reconstruction from purely 2D observations without explicit 3D supervision, bridging generative modeling with geometric reasoning in remote sensing.

 

your task

  • Masterthesis for Diffusion-based roof plane generation from very-high resolution imagery

 

your profile

  • Ongoing Master’s studies in Computer Science, AI, Computer Vision, Geoinformatics, or a related discipline
  • Programming experience in Python
  • Experience in AI and Deep Learning approaches
  • Experience with Pytorch or Tensorflow frameworks
  • Good communication skills and proficiency in English (spoken and written)
  • Basic knowledge of semantic segmentation and object detection is a plus

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

 

If you have any questions about this position (Vacancy-ID 5476) please contact:

 

Dr. Stefan Auer 
Tel.: +49 8153 28 1829 
Apply now