AI Radiology Evaluation Expert (Radiologist)

We're collaborating with a leading AI research lab to develop rigorous evaluations of how well AI interprets real radiology studies. The focus is on ensuring AI not only describes images fluently but also makes the clinically critical decisions—such as measurements by the correct convention, interval changes against prior studies, and structured categorization in borderline cases—where expert judgment is essential.

This is not about image labeling. Instead, it involves capturing the reasoning radiologists perform daily into reference standards that train and test advanced AI models.

Requirements

What you'd do:

• Read de-identified studies (including CT, MR, radiography, ultrasound, PET/CT, mammography, and more) and write the reference report or highlight specific findings.
• Apply structured systems and measurement conventions used in practice, such as RECIST, Lung-RADS, BI-RADS, CAD-RADS, ASPECTS, and others.
• Review AI-generated interpretations and identify inaccuracies, unsupported claims, or unsafe conclusions.
• Contribute cases that challenge even strong AI models.

Who we're looking for:

• Board-certified or board-eligible radiologists (e.g., ABR, FRCR, EDiR, or international equivalents). Residents and fellows in later stages of training may also be considered.
• Any diagnostic sub-specialty, including neuro, chest, abdominal, MSK, breast, cardiac, nuclear medicine, pediatric, and others.
• Currently reading studies or recently in active practice.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.