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Student Assistant Computer Vision/Deep Learning

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Student Assistant Computer Vision/Deep Learning

Telecommunications, Heinrich Hertz Institute

Student Assistant Computer Vision/Deep Learning

Skills

Deep LearningPythonPyTorchTensorFlowAIBlender

1 month ago

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Important information


Contract type:

Part time

Location:

Berlin, Germany

Work mode:

Remote

Published on:

7 September 2026

What they need


The Fraunhofer-Gesellschaft (www.fraunhofer.com) is one of the world's leading organizations for application-oriented research. 74 institutes develop pioneering technologies for our economy and society – more precisely: 30 000 people from technology, science, administration and IT. They know: Anyone who comes to Fraunhofer wants to and can make a difference. For themselves, for us and for the markets of today and tomorrow.

Future. Discover. Together.
The Computer Vision & Graphics group of the Vision & Imaging Technologies (VIT) department is looking for a student assistant in the area of deep learning for scene analysis in the construction domain/synthetic data creation and transformation. The group develops AI methods for 3D model creation, plan and scene analysis in the construction sector by analyzing as-built data (plans, images, point clouds) with artificial intelligence and integrating them into a BIM-based model. Become a part of our team and join us on our journey of research and innovation!

Be part of change

  • Support for the development and integration of 3D pose estimation and localization methods in the building sector
  • Creation of synthetic reference datasets and the development of Python scripts for the automatic creation and annotation of training data from real building models
  • Developing scripts for processing BIM and IFC data
  • Testing neural networks in the building domain
  • Creating interfaces between AI modules

What you contribute

  • Master's student in computer science or an equivalent subject at a Berlin university or college with above-average grades
  • Very good programming skills in Python and proficiency in graphics and computer vision libraries such as OpenCV and OpenGL, as well as deep learning frameworks such as Pytorch or Tensorflow
  • Good theoretical knowledge in the field of computer graphics and computer vision, as well as knowledge of 3D transformations and camera models
  • Ideally, basic knowledge of rendering engines (e.g., Blender, Unity, or Unreal Engine) or BIM (Building Information Management) systems
  • Structured way of working, both independently and within a team

What we offer

  • Fascinating challenges in a scientific and entrepreneurial setting
  • Attractive salary
  • Modern and excellently equipped workspace in central location
  • Great and cooperative working atmosphere in an international team
  • Opportunities to write a master's thesis
  • Flexible working hours
  • Opportunities to work from home

The position is initially limited to 1 year. An extension is explicitly desired.

The monthly working time is 80 hours. This position is also available on a part-time basis. We value and promote the diversity of our employees' skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable – for applicants with disabilities, we work together to find solutions that best promote their abilities. Remuneration according to the general works agreement for employing assistant staff.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

Ready for a change? Then apply now and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next.

If you require further information about this position, please contact:

Anna Hilsmann

[email protected]

Niklas Gard

[email protected]

Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute HHI

Requisition Number: 85480 Application Deadline: 10/15/2026

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