AI/ML for Biology Scientist
About The Position
Diseases of Aging & Regenerative Medicine (DARe) is seeking an AI/ML for Biology Scientist to advance the discovery of transformative therapies for diseases of aging, with a focus on neurodegenerative and cardiovascular diseases. The role integrates human pathobiology, experimental science, and machine learning to uncover disease mechanisms and identify, prioritize, and validate therapeutic targets. The scientist will develop, evaluate, and apply machine-learning approaches across human genetics, longitudinal electronic health record cohorts, high-resolution multi-omics, cellular imaging, and functional biology. The position calls for strong biological insight and expertise in modern machine learning, including representation learning, multimodal methods, biological foundation models, and reproducible model-development workflows. Working in a global, multidisciplinary environment, the scientist will partner with biologists, disease experts, and data scientists to shape experimental strategies, build scalable analytical workflows, and translate complex biomedical data into testable hypotheses and actionable evidence for drug discovery.
Requirements
- PhD in Computational Biology, Human Genetics, Bioinformatics, Data Science, Machine Learning, Systems Biology, or a related quantitative discipline.
- At least 3 years of experience applying computational and machine-learning approaches to biomedical research, translational science, or drug discovery.
- Hands-on experience modeling and analyzing diverse biomedical data, including genetic, single-cell, perturbation, spatial transcriptomics, and cellular imaging datasets.
- Experience evaluating, adapting, and applying biological foundation models to biomedical research, particularly for RNA, DNA, single-cell, or spatial data.
- Experience with model deployment (MLOps) and agentic frameworks.
- Strong programming skills in Python and R, and proficiency in modern data-science environments and developing reproducible workflows.
- Experience integrating complex biological datasets and translating them into actionable insights.
- Ability to collaborate effectively with experimental scientists.
- Demonstrated curiosity, learning agility, and willingness to work across disciplines.
Nice To Haves
- Strong experience in human genetics, including GWAS, rare variant analysis, Mendelian randomization, colocalization, or fine mapping.
- Real-world evidence experience, including longitudinal human cohorts, EHRs, and disease progression modeling.
- Familiarity with biomedical knowledge graphs, representation learning, or multimodal learning.
- Familiarity with biomedical ontologies, FAIR data principles, and data harmonization.
- Experience with biological aging clocks.
Responsibilities
- Partner with experimental scientists to understand biological questions and design data-driven approaches to answer them.
- Apply computational biology, human genetics, machine learning, and AI approaches to support target identification, prioritization, and validation for diseases of aging.
- Contribute to the design of large-scale experiments and data-generation strategies across genetics, multi-omics, imaging, and functional biology.
- Integrate diverse biological datasets to uncover disease mechanisms and generate therapeutic hypotheses.
- Help establish reproducible and scalable computational workflows and analytical approaches that accelerate discovery across DARe.
Benefits
- Performance-based cash incentive.
- Depending on the level of the role, eligibility to be considered for annual equity awards.
- Health, life, and disability benefits.
- 401(k) with company contribution and match.
- Vacation, personal days, holidays, and other leaves.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
