Principal Scientist, AI-Driven Oncology Target Discovery
Core
Drive identification of novel therapeutic targets and resistance mechanisms in oncology by integrating multimodal biological, clinical, and real-world datasets to generate actionable insights for target nomination and portfolio strategy.
Role type
Principal Computational Scientist (AI/ML)
Builds
Agentic AI and machine learning systems for scalable, end-to-end target discovery workflows
Domain
Oncology drug discovery, computational biology, machine learning
Deliverable
production ML models
Required skills
Machine learning, agentic AI, multimodal data integration, functional genomics, systems biology, target identification, scientific reporting, cross-functional leadership
Preferred skills
Ph.D. in computational biology or related quantitative field, single-cell and spatial omics expertise, LLM-driven application development, oncology disease biology, publication record in computational biology
Technologies
Agentic AI frameworks, LLMs, omics data platforms, real-world data analytics tools
Responsibilities
Drive integration of computational approaches into cross-functional target discovery workflows; Lead design and deployment of agentic AI and ML systems; Integrate and analyze multimodal patient-derived datasets; Translate analytical outputs into decision-ready insights for Go/No-Go recommendations; Author scientific reports and present methods to publishable standards
Seniority
Principal, hands-on IC with strategic influence
