Radiologists: Medical Image Review for AI Benchmarks ($210/hr)

What you'll do

You act as the human reference for a benchmark. Terac's study asks you to read de-identified images and linked clinical cases on a secure remote platform, give your expert read, and fill in a structured scoring rubric for each case. You also highlight the key anatomical or pathological findings behind your read.

The point is not to treat patients but to set the ground truth that diagnostic imaging algorithms are later measured against. Your reads become the baseline, so careful, consistent rubric use matters more than speed.

Who fits

• Licensed, practicing radiologists with strong clinical diagnostic experience
• General radiologists, neuroradiologists, musculoskeletal radiologists and other imaging subspecialists are all welcome
• Comfort applying standardized rubrics to complex cases

The ad lists no location requirement (it is open worldwide), no minimum years and no language, though the platform is presumably in English.

What it pays

$210 per hour, stated on the listing. The ad does not say how many hours of cases are available or how time is counted, so ask about the volume of work once you are matched. This is the highest-paying of the three radiology studies Terac currently lists; the resident versions pay $90 and $105 per hour.

Worth knowing

Good:

• High stated hourly rate for work that uses your clinical skills directly
• Fully remote and asynchronous, so you review cases at your own pace
• Open worldwide per the listing

Less good:

• The ad does not say how many cases or hours are available
• Registering with Terac does not guarantee you are matched to this study
• The ad does not name the end customer or the algorithms being benchmarked
• Reads are used as reference standards, so expect your work to be held to a rubric rather than left to personal style

About this listing

The Apply button opens this study on Terac; you sign in or create a Terac account there to apply. The listing runs until 21 December 2026. Terac's own pages describe its onboarding in more detail on the company page. See Terac.