Associate Principal Scientist, AI-Pathology
Core
Apply advanced computational pathology and AI to multimodal digital pathology datasets to derive biological insights for drug safety prediction and support drug portfolio milestone decision making.
Role type
Associate Principal Scientist (AI-Pathology)
Builds
Multimodal foundation models integrating pathology, omics, and chemical/ADME features for drug safety
Domain
Biopharmaceuticals / Computational Pathology / AI
Deliverable
production ML models
Required skills
PhD in Computer Vision & AI, hands-on ML/DL (PyTorch), self-supervised learning, multiple-instance learning (MIL), advanced Python, WSI dataset preparation, computational pathology model delivery
Preferred skills
Omics/Cell Painting experience, biomedical imaging datasets, cloud computing, workflow automation
Technologies
PyTorch, Python, WSI, multi-GPU/cloud environments, distributed training, containers, feature stores, experiment tracking
Responsibilities
Prepare and standardize WSI data (stain/scan harmonization, augmentation, QC, tiling), build multi-resolution architectures for morphological feature learning, train self-supervised foundation models on multi-scale WSIs, implement weak/MIL strategies, operate multi-GPU/cloud environments for scalable distributed learning, benchmark representation quality and cross-site generalization, integrate multimodal representations (pathology, omics, chemical features), support unified drug safety risk scores via ensembling/meta-learning, collaborate with pathologists and SMEs for interpretability and milestone planning
Seniority
Associate Principal, hands-on IC with strategic impact
