Principal Scientist, Imaging Analytics

Role: Principal Scientist specializing in Imaging Analytics within Interventional Oncology (INTO), focusing on medical imaging AI applications for early-phase oncology trials. Responsibilities: lead development and application of AI models (segmentation, radiomics, multimodal prediction) on CT, MRI, PET data; collaborate with external vendors, CROs, academic partners to innovate foundational imaging AI; translate complex quantitative imaging findings into actionable insights for clinical decision-making; publish research and present at major scientific meetings. Requirements: Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, or related field; 3+ years of industry or post-doctoral experience in medical imaging AI; proficiency in deep learning frameworks (Python, PyTorch), medical imaging libraries (MONAI, SimpleITK, nnU-Net), and cloud MLOps; extensive experience with DICOM workflows and 3D image analysis; strong publication record. Preferred: experience with solid-tumor imaging (lung, H&N), clinical trial endpoints (RECIST, PERCIST), and platform scaling. HighValue: Oncology (solid tumors), early-phase trials, AI-driven response assessment, dose optimization, cross-disciplinary collaboration. Location: New Brunswick/Raritan, NJ; Spring House/Horsham, PA; or Boston, MA.