At Johnson & Johnson, the business problem is to develop novel cancer therapies by applying Radiology AI/ML to oncology research, leveraging real-world imaging datasets with comprehensive clinical data to design, develop, and validate models for disease characterization and outcome prediction.
Requirements
- Proficiency in radiology imaging modalities such as CT, PET, MRI, etc.
- Demonstrated experience driving research in and applying Computer Vision techniques, such as Foundation models, Transformers, CNNs, Diffusion models, RNNs, GANs, and radiomics.
- Extensive experience with traditional Computer Vision applications, such as OpenCV, object detection, edge detection, image segmentation
- Extensive hands-on experience with medical imaging modalities and formats (e.g., DICOM, nrrd, nifti) and collaborating with subject matter experts.
- Proficiency with one or more programming languages such as Python or C++
- Experience applying Radiology AI/ML in clinical settings.
- Hands-on technical data analysis, cloud computing (AWS, Azure), dockerization.
Responsibilities
- Conceive, develop, and implement analytics and AI/Machine learning radiology solutions to high-priority scientific problems
- Extract insight from complex, unstructured radiology image or other imaging modalities data to enhance decision making in clinical development of cancer therapy (e.g., tumor characterization, outcome prediction, etc.)
- Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making
- Design, develop, and validate models leveraging unique real-world imaging datasets with comprehensive clinical data enriched with expert annotations
- Apply Radiology AI/ML to oncology research
- Work on teams that save lives by developing the medicines of tomorrow
- Pioneer the path from lab to life while championing patients every step of the way
Other
- Ph.D. degree in a quantitative discipline (e.g., artificial intelligence, computer science, applied mathematics, electrical engineering, or similar), or closely related field, completed within the past 3 years, or to be completed within the next 6 months.
- Strong publication record and ability to effectively communicate technical work to a wide audience
- Exposure to oncology, preferably solid tumors such as lung cancer.
- Familiarity with and exposure to drug discovery and clinical development processes
- Experience working closely with healthcare professionals
