In collaboration with the Biomarkers of Aging Consortium, we are co-developing Biolearn, an open-source library for biomarkers of aging data analysis. With Biolearn, researchers can easily load public datasets, apply and compare aging clocks/models, and test new computational methods to study biological age and healthspan metrics.

Through this ongoing effort, participants have designed functions and tools that provide insights into biomarkers of aging, enabling researchers to explore DNA methylation data, assess biological clocks, and study age-related biomarkers with precision. Participants have also ported and unified publicly available aging datasets and models, expanding Biolearn’s utility as a comprehensive and standardized platform for aging research.

Apply for exciting endeavor to accelerate advancements in aging research through the power of open-source collaboration! Participants will contribute to the development of the library by implementing aging models, integrating public datasets, and developing analytical tools that enhance the analysis and interpretation of biomarkers of aging.

What You’ll Gain:
• Hands-on experience in open-source software development and data science
• Recognition as an official contributor to Biolearn
• Opportunities to collaborate with longevity researchers and attend exclusive events

Desired Skills:
• Proficiency in Python, object-oriented programming, open-source biological dataset handling.
• Familiarity with Git, and GitHub, Jupyter Notebooks
• Interest in aging research, software engineering, bioinformatics, or computational biology.
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Timeline:
• October 6 – December 6, 2025; Weekly online meetings; 3-5 hours/week

Application & Selection Process:
• Interested students must apply first by completing the Fall 2025 application
• Applicants selected for the next stage will receive materials and instructions for completing two brief deliverable tasks
• Final participants will be chosen based on demonstrated readiness and engagement.