Principal Scientist, Imaging Analytics

Scorpion Therapeutics; Spring House (PA); On-site; USD 150,000 - 200,000; Full time

Job summary

Johnson & Johnson's Innovative Medicine division seeks a Principal Scientist in Imaging Analytics to apply AI to medical imaging (CT, MRI, PET) for early-phase oncology trials, developing quantitative imaging metrics and translating imaging data into actionable clinical insights to support drug development decisions.

You will lead end-to-end AI applications on trial imaging data, collaborate with internal teams and external partners to validate imaging AI models, and share findings through

Qualifications

• Ph.D. in relevant field required with 3+ years postdoc/industry experience in medical imaging AI.
• Proficiency in Python and PyTorch; experience with MONAI and nnU-Net is preferred.
• Strong track record of publications and excellent communication skills.

Responsibilities

• Lead end-to-end AI applications on trial imaging data across oncology programs.
• Collaborate with internal teams and external partners to validate imaging AI models.
• Disseminate findings through publications and conferences; bridge data science with clinical development.

Skills

Python

PyTorch

Cloud MLOps

Publications

Communication

Education

Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, or related field

Tools

MONAI

nnU-Net

Job description

Role:

Principal Scientist in Imaging Analytics within Johnson & Johnson's Innovative Medicine division, focusing on applying AI to medical imaging (CT, MRI, PET) for early-phase oncology trials. Objectives include developing AI-derived quantitative imaging metrics, advancing foundational imaging AI capabilities, and translating complex imaging data into actionable clinical insights to support drug development decisions. Responsibilities encompass leading end-to-end AI applications on trial imaging data, collaborating across internal teams and external partners to innovate and validate imaging AI models (e.g., segmentation, radiomics, multimodal modeling), and disseminating findings through publications and conferences. The role bridges data science, clinical development, and external collaborations.

Qualifications:

Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, or related field; 3+ years postdoctoral or industry experience in medical imaging AI; proficiency in Python, PyTorch, and imaging libraries such as MONAI and nnU-Net; extensive experience with medical imaging workflows and cloud MLOps; strong publication record and communication skills.

Preferred:

experience with tumor imaging (lung, head & neck), oncology clinical trials, and endpoints like RECIST.

Location:

The position is based in the US (New Brunswick, Raritan, Spring House, or Boston) with no explicit travel requirement mentioned.