Senior Scientist, Imaging Analytics
Horsham, PAAll locationsHorsham, PACambridge, Massachusetts, United States of AmericaSpring House, Pennsylvania, United States of AmericaNew Brunswick, New Jersey, United States of AmericaRaritan, NJBoston, MA Hybrid
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About the role
We are seeking a Senior Scientist, Imaging Analytics to join Interventional Oncology (INTO) and support the scientific application of medical imaging AI across our early-phase oncology portfolio. In this role, you will transform routinely collected oncology trial scans (CT, MRI, PET) into earlier, evidence-based clinical-development decisions. You will advance foundational imaging-AI capabilities, develop novel quantitative imaging metrics, and deliver insights that enhance response assessment, dose optimization, and go/no-go decisions. This is a high-impact, high-visibility role for a scientist who is passionate about translating cutting-edge imaging AI from research into real-world clinical impact. You will serve as a scientific bridge across data science, clinical development, and external partners. This position can be based in New Brunswick/Raritan, NJ; Spring House/Horsham, PA; or Boston, MA. This position is eligible to participate in the Company’s long-term incentive program.
What you'll bring
- · Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, or a related quantitative field.
- · Hands-on expertise across the medical imaging AI stack: deep learning (segmentation, detection, classification, registration), radiomics, and multimodal predictive modeling.
- · Proficiency in Python and PyTorch, with practical experience in medical-imaging libraries such as MONAI, SimpleITK, ITK, PyRadiomics, nnU-Net, 3D Slicer, and OpenCV.
- · Experience with cloud ML infrastructure and MLOps practices for scalable training and inference on imaging data.
- · Extensive experience with the full imaging data workflow: DICOM I/O, visualization, registration, harmonization, annotation, and segmentation of 3D medical images.
- · Strong peer-reviewed publication record and demonstrated ability to communicate complex scientific concepts to both technical and cross-functional audiences.
- · Post-doctoral or industry experience developing AI/ML for medical imaging (CT, MRI, PET) in a clinical setting.
- · Experience in analyzing solid-tumor imaging, particularly lung and head & neck (H&N).
- · Track record of developing and applying AI/ML to oncology imaging and within oncology clinical trials.
- · Familiarity with standard oncology endpoints (e.g., RECIST 1.1, iRECIST, PERCIST).
- · Experience building and scaling clinical or imaging AI platforms end-to-end, including data ingestion, harmonization, model inference, visualization, and continuous monitoring.
- Experience in sourcing, structuring, and managing external partnerships with imaging-AI vendors, CROs / imaging core labs, biomarker companies, and academic centers.