Director, AI and Machine Learning for Biology

What you'll do

• Set AI strategy and prioritize initiatives, measures, and investments that improve target decisions and accelerate discovery.
• Lead development and application of biological foundation models, multimodal learning, knowledge graphs, and agentic workflows for evidence integration and target prioritization.
• Build and develop a US-based multidisciplinary team, foster collaboration, and establish external partnerships.

What they ask for

• PhD in Machine Learning, Computational Biology, Data Science, Computer Science, Systems Biology, or a related quantitative discipline, combined with deep understanding of biology.
• 10+ years applying advanced computational and AI approaches to biomedical research, drug discovery, or translational medicine.
• Proven success leading multidisciplinary global teams across AI, human data, and experimental science.
• Experience developing or applying advanced machine-learning approaches to complex biological data, plus strong coding proficiency in Python and deep learning frameworks.

Nice to have

• Expertise in statistical genetics or therapeutic areas including diseases of aging, neurodegeneration, cardiometabolic disease, or regeneration biology.
• Experience with knowledge graph technologies or developing biological aging clocks.

Pay

$194,600.00 - $361,400.00 per year (base salary)

Tools

Python, deep learning frameworks, version control systems, ETL/ELT pipelines, biomedical ontologies, knowledge graph technologies, machine learning operations frameworks

AI focus

Shape AI strategy and use biological foundation models, multimodal and generative AI, machine learning, knowledge graphs, and agentic workflows to integrate biomedical evidence and support target identification, prioritization, and validation.