Student Assistant Computer Vision/Deep Learning

Fraunhofer Gesellschaft; Berlin; Hybrid; EUR 11.000 - 12.000; Teilzeit

Benefits dieser Stelle

Opportunities to work from home

Master thesis option

Modern workspace in central Berlin

Zusammenfassung

Fraunhofer-Gesellschaft in Berlin seeks a Master’s student in computer science to contribute to deep learning for scene analysis in the construction domain. You will help develop 3D pose estimation, generate synthetic datasets, and script BIM/IFC data processing within a growing research team.

The role offers flexible, partial remote work options and opportunities to work with PyTorch/TensorFlow, OpenCV, and OpenGL, alongside expert colleagues in a scientific environment.

Qualifikationen

• Master's student in computer science or equivalent at a Berlin university
• Strong Python skills and experience with OpenCV, OpenGL and DL frameworks (PyTorch or TensorFlow)
• Solid knowledge of 3D transformations, camera models and graphics concepts
• Nice-to-have: rendering engines (Blender/Unity/Unreal) or BIM systems
• Structured, independent and team-oriented work style

Aufgaben

• Assist in developing 3D pose estimation and localization methods for building domain
• Create synthetic reference datasets and Python scripts for automatic data annotation
• Develop scripts to process BIM/IFC data
• Test neural networks in building domain settings
• Create interfaces between AI modules

Kenntnisse

Python

OpenCV

OpenGL

PyTorch

TensorFlow

3D graphics

BIM knowledge

Deep learning

Unit testing

Ausbildung

Master's student in computer science

Tools

Blender

Unity

Unreal Engine

OpenGL tools

BIM software

Jobbeschreibung

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The Fraunhofer-Gesellschaft (www.fraunhofer.com ) is one of the world's leading organizations for application-oriented research. 74institutes develop pioneering technologies for our economy and society – more precisely: 30000 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
• Modern and excellently equipped workspace in central location
• Great and cooperative working atmosphere in an international team
• Opportunities to write a master's thesis
• 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.

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

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