AI/ML for Biology Scientist

What you'll do

• Partner with experimental scientists to design data-driven studies and large-scale experiments.
• Apply computational biology, genetics, and machine learning to integrate biological datasets and generate therapeutic hypotheses.
• Develop reproducible, scalable analytical workflows that support target discovery and validation.

What they ask for

• PhD in a relevant quantitative discipline.
• 3+ years applying computational and ML approaches to biomedical research, translational science, or drug discovery.
• Hands-on modeling and analysis of diverse biomedical data, including genetic, single-cell, perturbation, spatial transcriptomics, and cellular imaging data.
• Experience applying biological foundation models; ML deployment (MLOps) and agentic frameworks; strong Python and R programming skills.

Nice to have

• Strong human genetics experience, such as GWAS, rare variant analysis, Mendelian randomization, colocalization, or fine mapping.
• Experience with longitudinal cohorts/EHRs, biomedical knowledge graphs, multimodal learning, FAIR data, or biological aging clocks.

Pay

$126,000 and $234,000 USD annually (base salary); $138,600 and $257,400 USD annually (base salary)

Tools

Python, R, EHRs, GWAS, MLOps

AI focus

Applies machine learning, multimodal methods, representation learning, and biological foundation models to biomedical data for disease-mechanism discovery and therapeutic target identification, prioritization, and validation.