Student Assistant (HiWi) (f/m/div) for AI-Assisted 3D Segmentation of Photonic Nanostructures

The position offers hands-on experience in scientific image processing, AI-assisted segmentation and three-dimensional analysis of biological nanostructures. Possible tasks include:

• Performing 3D segmentation of individual guanine crystals based on Cryo-FIB microscopy datasets using Amira software.
• Applying and optimizing machine-learning-based, automated and semi-automated segmentation workflows.
• Refining segmentation results manually where necessary to ensure accurate separation of individual crystals.
• Ensuring a consistent segmentation approach across datasets representing the three color states (blue, green and orange).
• Preparing segmented 3D datasets for quantitative analysis of crystal spacing and spatial organization, and for computational modelling of their optical response across different color states.
• Documenting image-processing workflows and organizing datasets for reproducible analysis.

Training and guidance in Amira and the relevant segmentation methods will be provided!

We are looking for motivated students pursuing a degree in materials science, computer science, biomedical engineering, physics, biology or a related field. Applicants should

• Be currently enrolled at a German university.
• Have an interest in scientific image processing, 3D visualization or materials characterization.
• Demonstrate a careful, systematic and independent working approach.
• Have good oral and written communication skills in English.
• Be able to work on site at the Max Planck Institute for Intelligent Systems in Stuttgart.

We are especially interested in applicants who have:

• Previous experience with 3D image processing or segmentation software, such as Amira, Avizo, Dragonfly, VGSTUDIO MAX or Materialise Mimics.
• Interest in machine learning and AI-assisted image analysis.
• An interest in microscopy, materials science, biomaterials or photonic nanostructures.