Digital Pathology Annotator

We’re looking for a detail-oriented Digital Pathology Annotator to support ongoing data generation for AI model development. This role focuses on high-quality annotation of histopathology images (H&E and IHC) across multiple oncology indications.

Your work will directly impact model performance, making precision, consistency, and attention to detail critical. This is a hands-on role centered on structured annotation tasks and adherence to defined protocols.

Responsibilities:

• Annotate whole slide images (H&E, IHC) using tools such as QuPath
• Identify and label tumor regions, stromal components, immune cells, and relevant biomarkers
• Follow strict annotation protocols and class definitions
• Ensure consistency and accuracy across large volumes of data
• Maintain high-quality outputs aligned with model training requirements
  
  

• Background in pathology, histology, or a related biomedical field
• Hands-on experience with digital pathology tools (QuPath preferred)
• Strong understanding of tissue morphology and staining patterns (H&E, IHC)
• High attention to detail and ability to follow structured guidelines
• Ability to work independently and meet defined quality thresholds
  
  

• Location: Tel Aviv (close to train and light rail)
• Employment type: Part-time, flexible capacity (ideal for students), hourly contract