Key Responsibilities
Machine Learning & Deep Learning
- Develop and implement machine learning and deep learning models for medical imaging tasks such as segmentation, classification, anomaly detection, and quantitative analysis
- Work with clinical datasets to ensure model accuracy and relevance
Medical Imaging Data Expertise
- Handle 2D/3D DICOM datasets and perform image reconstruction, preprocessing, and annotation
- Integrate imaging data with PACS systems for workflow optimization
- Utilize medical imaging libraries for analysis and visualization
Technical Stack & Model Deployment
- Develop models using Python, TensorFlow, PyTorch, and other relevant libraries
- Build, validate, and deploy clinical-grade AI/ML models with explainability and compliance considerations
- Collaborate with clinical and technical teams to ensure safe and effective implementation
Validation & Compliance
- Ensure models meet regulatory, compliance, and clinical validation standards
- Conduct quantitative analysis to support clinical decision-making and reporting
- Maintain documentation for audits and model lifecycle management
