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AI​/ML Biology Scientist

Job in San Diego, San Diego County, California, 92189, USA
Listing for: Novartis AG
Full Time position
Listed on 2026-10-20
Job specializations:
  • Research/Development
    Data Scientist
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer, Data Analyst, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 126000 - 234000 USD Yearly USD 126000.00 234000.00 YEAR
Job Description & How to Apply Below
Position: AI/ML for Biology Scientist
Job Description Summary

Diseases of Aging & Regenerative Medicine (DARe)

DARe is seeking a talented AI/ML for Biology Scientist to advance the discovery of transformative therapies for diseases of aging. The role will integrate human genetics, longitudinal health data, multi-omics, imaging and functional biology with modern machine learning to uncover human disease mechanisms and identify, prioritize and validate therapeutic targets for diseases of aging with a focus on neurogenerative and cardiovascular diseases.

Job Description

Internal

Job Title:

Senior Expert I/II Data Science

Position Location:

San Diego, CA Hybrid

About the Role

Aging is the biggest risk factor for chronic diseases. The new AI for biology scientist will advance DARe’s mission to discover novel transformative therapies for diseases of aging by integrating at scale human pathobiology, experimental science and machine learning.

The role will develop, evaluate and apply machine-learning approaches across human genetics, longitudinal EHR cohorts, high resolution multi-omics technologies, cellular imaging and functional data to uncover disease mechanisms and drive therapeutic target identification, prioritization and validation. The successful candidate will combine strong biological insight with 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 new team member 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.

Key Responsibilities
  • Partner closely with experimental scientists to understand biological questions and design data-driven approaches to answer them.
  • Apply expertise in computational biology, human genetics, machine learning and AI approaches to support target identification, prioritization and validation for disease 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.
Essential Requirements
  • 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 with modeling and analyzing diverse biomedical data types including genetic, single cell, perturbation datasets, spatial transcriptomics, and cellular imaging.
  • Experience evaluating, adapting, and applying biological foundation models to biomedical research, particularly RNA, DNA, single-cell, or spatial data.
  • Experience with Model deployment (MLops) and agentic frameworks Strong programming skills in Python and R and proficient in working in modern data-science environments and developing reproducible workflows.
  • Experience integrating complex biological datasets and translate into actionable insights.
  • Ability to collaborate effectively with experimental scientists.
  • Demonstrated curiosity, learning agility and willingness to work across disciplines.
Desirable Requirements
  • Strong experience in human genetics, including GWAS, rare variant analysis, Mendelian randomization, colocalization or fine mapping.
  • RWE experience including longitudinal human cohorts, EHRs and…
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