Your Skills

• Bachelor’s-Degree or vocational training in radiology technology, biomedical engineering, medical imaging, or a related field.
• Practical experience with 3D Slicer (or similar platforms such as ITK-SNAP, MITK or Materialise Mimics) and a solid understanding of CT and MRI modalities.
• Strong skills in manual 3D segmentation and interest in developing semi-automated annotation methods.
• Familiarity with medical image data and formats (DICOM, NIfTI, nrrd) and basic image processing concepts.
• Experience with Python and related image pro cessing libraries (e.g., Scikit-Image, Simple-ITK, SciPy)
• A meticulous working style is essential for high-quality annotations
• Team-oriented mindset and clear communication with both technical and clinical stakeholders.
• Self-driven, motivated and proactive personality

Your Tasks

In this position you will be a key contributor to the creation of high-quality, annotated medical imaging datasets that
underpin our deep learning and clinical research projects. Your responsibilities include:

• Manual 3D segmentation of anatomical structures and pathologies in CT and MRI scans using 3D-Slicer.
• Developing and refining semi-automated segmentation methods, such as threshold-based, region-growing, or AI-assisted workflows, to improve annotation speed and consistency.
• Establishing and documenting standard operating procedures (SOPs) and quality-control guidelines for reproducible labeling.
• Close collaboration with our interdisciplinary team members to ensure that annotations meet clinical and research requirements.
• Maintaining and curating annotated datasets, ensuring compliance with data protection and medical device regulations (e.g., GDPR, MDR).

Your Salary