Remote Radiologist Chest CT Annotation for AI Projects

Aptura

United States

Remote

USD 83,000 - 124,000

Part time

14 days+

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Benefits offered by this job

Flexible scheduling
Remote work
Weekly pay

Job summary

AI Trainer Jobs seeks a radiologist with a chest/thoracic background to perform structured annotations on de-identified chest CT scans. You will mark points, boxes, and measurements on findings, following strict annotation guidelines to ensure spatial accuracy.

This is a remote, flexible, short-term project with asynchronous work on a dedicated platform. Ideal candidates have 3–10 years in radiology, a license, and native or near-native English, enabling precise, rule-based annotations while

Qualifications

  • Must be a registered radiologist with an active license.
  • 3–10 years of radiology experience with a chest/thoracic focus.
  • Strong grounding in thoracic anatomy and cross-sectional CT.
  • Proven accuracy and consistency in image review or measurement work.

Responsibilities

  • Mark coordinates on scans, such as the centre of a nodule.
  • Draw bounding boxes around regions of interest.
  • Record measurements on segmentations or polygons already drawn.
  • Apply annotation guidelines consistently across studies.
  • Flag ambiguous cases with a brief rationale for guidelines refinement.

Skills

Attention to detail
English proficiency
Technical annotation tools
Image review accuracy

Education

Active radiologist license
3–10 years radiology experience

Tools

Annotation platform
Digital imaging viewers

Job description

AI Trainer Jobs seeks a radiologist with a chest/thoracic background to perform structured annotations on de-identified chest CT scans. You will mark points, boxes, and measurements on findings, following strict annotation guidelines to ensure spatial accuracy.

This is a remote, flexible, short-term project with asynchronous work on a dedicated platform. Ideal candidates have 3–10 years in radiology, a license, and native or near-native English, enabling precise, rule-based annotations while

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