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 disease progression modelling. 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. Compensation & Benefits: The salary for this position is expected to range between $126,000 and $234,000 USD annually for Senior Expert I, Data Science, and $138,600 and $257,400 USD annually for Senior Expert II, Data Science. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves. To learn more about the culture, rewards and benefits we offer our people click here . EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. Accessibility and reasonable accommodations The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to [email protected] or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message. Salary Range $126,000.00 - $234,000.00 Skills Desired Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis