Senior Scientist II, Computational Pathology, Precision Medicine Pathology

Job Responsibilities:
- Develop, train, and validate machine learning models for tissue image analysis (segmentation, object detection, classification).
- Apply deep learning and representation learning to solve digital pathology challenges.
- Curate and maintain large-scale pathology datasets to ensure data quality and integrity.
- Develop and implement tools and pipelines for data preprocessing, feature engineering, and model deployment.
- Collaborate with pathologists, biologists, statisticians, data analysts, and engineers to integrate ML into existing workflows.
- Assist with external research collaborations.
- Evaluate histopathology and spatial omics datasets to identify biomarkers for patient stratification and companion diagnostics.
- Stay current on AI/ML and digital pathology advances and apply insights to ongoing projects.

Qualifications:
Required:
- Ph.D. (or M.S. with 5+ years) in CS, EE, Computational Biology, Bioinformatics, or related field with emphasis on computer vision/ML.
- Image analysis experience (segmentation, object detection, classification) demonstrated via publications, open-source, or products.
- Python; experience with OpenCV and ML frameworks (TensorFlow, PyTorch).
- MLOps experience (deployment, monitoring, lifecycle management).
- Cloud and scalable AI/ML pipelines (AWS, Azure, GCP).
- Excellent communication across interdisciplinary teams.
- Strong problem-solving skills.
Preferred:
- Exposure to digital pathology/biomedical imaging.
- Experience with spatial omics and/or integrating molecular data with image analysis.
- Knowledge of precision medicine/biomarker discovery/personalized treatment.
- Familiarity with cell/molecular biology in oncology, immunology, or cancer immunotherapy.

Benefits/Instructions:
- Paid time off (vacation, holidays, sick), medical/dental/vision insurance, 401(k) (eligible employees).
- Eligible for long-term incentive programs.