Careers

About Imagene

Imagene AI is democratizing precision medicine with multi-modal foundation models and an end-to-end OI Suite. At the core of our technology is a Living Intelligence Engine that continuously integrates and learns from imaging, molecular, and clinical data, making every clinical trial more responsive, every insight more actionable, and every patient journey more personalized.

Our OI Suite is a transformative platform that empowers researchers, clinicians, and pharmaceutical partners across the full spectrum of oncology innovation, from biomarker discovery to patient identification. Our first product, LungOI, is an AI-powered multi-gene test for NSCLC that rapidly profiles biomarkers directly from a standard biopsy image, enabling faster and more informed clinical decisions.

Powered by our state-of-the-art multimodal foundation models- trained on over 1.5 million tissue samples from more than 40 organs and tissue types, along with diverse biological modalities-Imagene AI enables cutting-edge research, especially in data-limited settings.
We are committed to advancing precision medicine and expanding its impact across cancer and beyond. If you are passionate about transforming patient care through AI and innovation, we invite you to join us on this meaningful journey.

Array

Digital Pathology Annotator

Tel Aviv · Part-time · Entry-level

About The Position

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

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


Position terms (review before applying):

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

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