Senior Scientist II, Computational Pathology, Precision Medicine Pathology

What you'll do

• Develop, train, and validate machine learning models for tissue image segmentation, object detection, and classification.
• Apply deep learning and representation learning techniques to solve complex challenges in digital pathology.
• Curate and maintain large-scale pathology datasets to ensure data quality for model training and evaluation.
• Build and implement pipelines for data preprocessing, feature engineering, and model deployment.
• Analyze histopathology and spatial omics datasets to identify biomarkers for patient stratification and companion diagnostics.
• Integrate machine learning solutions into existing workflows by collaborating with pathologists, biologists, and statisticians.
• Monitor and manage the lifecycle of machine learning models in production environments using MLOps practices.

What we're looking for

• A Bachelor's degree with 12 years of experience, a Master's degree with 10 years of experience, or a PhD with 4 years of experience is required.
• Experience in image analysis techniques including segmentation, object detection, and classification is required.
• Proficiency in Python and experience using computer vision libraries like OpenCV and ML frameworks like TensorFlow or PyTorch are required.
• Familiarity with MLOps practices for deployment, monitoring, and lifecycle management of models in production environments is required.
• Familiarity with cloud computing platforms and scalable AI/ML pipelines such as AWS, Azure, or GCP is required.
• Excellent communication skills to explain technical concepts to interdisciplinary teams are required.
• Exposure to digital pathology or biomedical imaging such as histopathology or microscopy is preferred.
• Experience with spatial omics data, precision medicine, or cell and molecular biology concepts is preferred.