Associate Director, Oncology Ai Imaging Biomarkers
Johnson & Johnson
Cambridge, Massachusetts, United States of America
$137,000 to $235,750; bonus eligible; medical, den...
Hybrid
Ai-based biomarkers
Digital image analysis
Computer vision
Johnson & Johnson is seeking an Associate Director for Oncology AI Imaging Biomarkers to advance AI-driven biomarker research within their Oncology R&D portfolio. The ideal candidate will have extensive experience in computational pathology, computer vision, and AI applications, with a focus on developing innovative solutions for cancer treatment.
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Job Summary
Support the strategic and technical advancement of AI-based biomarkers within J&J’s Oncology R&D portfolio.
Collaborate with internal teams to integrate digital biomarker insights into drug development and precision medicine diagnostic strategies.
The anticipated base pay range for this position is $137,000 to $235,750, with eligibility for an annual performance bonus and comprehensive benefits.
Matching Summary
Match Score: 85
Johnson & Johnson is seeking an Associate Director for Oncology AI Imaging Biomarkers to advance AI-driven biomarker research within their Oncology R&D portfolio. The ideal candidate will have extensive experience in computational pathology, computer vision, and AI applications, with a focus on developing innovative solutions for cancer treatment.
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Salary
$137,000 to $235,750; Bonus eligible; Medical, dental, vision, life insurance, disability, retirement plan, savings plan, vacation, sick time, holiday pay, personal and family time
Skills & Requirements
Must-have
AI-based biomarkers
digital image analysis
computer vision
AI/ML applications in pathology
Oncology Computer Vision applications
Nice-to-have
organizational change
project delivery
managing external vendors
diagnostic product development
Key Requirements
PhD or equivalent advanced degree
5+ years of business experience
experience in computational pathology
experience in computer vision
experience in tissue image analysis workflows
experience in AI-enabled diagnostic product development