AI/ML for Biology Scientist

What you'll do

• Develop and apply machine learning approaches to human genetics, multi-omics, and cellular imaging data.
• Identify, prioritize, and validate therapeutic targets for diseases of aging, specifically neurogenerative and cardiovascular diseases.
• Integrate diverse biological datasets to uncover disease mechanisms and generate testable therapeutic hypotheses.
• Design large-scale experiments and data-generation strategies across genetics and functional biology.
• Build scalable, reproducible computational workflows and analytical approaches to accelerate drug discovery.
• Evaluate and adapt biological foundation models for RNA, DNA, single-cell, or spatial data.
• Translate complex biomedical data into actionable evidence for drug discovery and experimental strategies.

What we're looking for

• PhD in Computational Biology, Human Genetics, Bioinformatics, Data Science, Machine Learning, Systems Biology, or a related quantitative discipline.
• 3+ years of experience applying computational and ML approaches to biomedical research, translational science, or drug discovery.
• Hands-on experience modeling and analyzing genetic, single-cell, perturbation, spatial transcriptomics, and cellular imaging datasets.
• Experience evaluating, adapting, and applying biological foundation models to RNA, DNA, single-cell, or spatial data.
• Experience with MLops model deployment and agentic frameworks.
• Strong programming skills in Python and R to develop reproducible workflows in modern data-science environments.
• Strong experience in human genetics, including GWAS, rare variant analysis, Mendelian randomization, colocalization, or fine mapping (preferred).
• RWE experience including longitudinal human cohorts, EHRs, and disease progression modeling (preferred).