Position Summary
The Buck Institute for Research on Aging is seeking a full-time
Bioinformatics and Data Scientist or Postdoctoral Researcher to join a collaborative research team focused on aging, multi-omics, computational biology, and translational data science.
This position offers a unique opportunity to work in an academic research environment with a close-knit, interdisciplinary team while collaborating with leading experts in aging biology, bioinformatics, clinical research, and computational science. The successful candidate will contribute to a five-year government-funded project focused on advancing computational and multi-omics approaches to better understand human aging, biological resilience, and healthspan. This role will support broader nationwide efforts to develop data-driven approaches that may ultimately improve how aging and age-related disease risk are measured, modeled, and addressed.
The ideal candidate will have strong experience in bioinformatics, statistics, computational biology, human omics data analysis, and scientific communication. The position is well suited for an independent, highly motivated scientist who enjoys working across disciplines and contributing to both discovery-driven and translational research.
Key Responsibilities
1. Perform bioinformatics and data science analyses.
The successful candidate will analyze diverse biological and clinical datasets, including but not limited to:
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Proteomics
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Metabolomics
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Methylomics
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Survey data
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Integrative multi-omics datasets
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Human biological aging and omics-clock data
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Drug repurposing analyses
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Enrichment and pathway analyses
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Dimensionality reduction and clustering
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Classification methods, including random forests and support vector machines
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Neural network-based approaches
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Simple and multiple linear regression
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Parametric and non-parametric statistical analyses
2. Analyze, curate, and manage research data
Responsibilities will include:
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Curating, organizing, and preparing data for analysis and upload to central repositories
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Supporting data harmonization across projects, cohorts, and collaborators in accordance with data use agreements
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Reviewing and improving standard operating procedures for data transfer, quality control, and management
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Coordinating with internal and external teams to ensure timely collection, transfer, and analysis of data
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Attending project meetings and contributing to improvements in data workflows, systems, and documentation
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Ensuring data quality, reproducibility, and compliance with project requirements
3. Collaborate with scientific and administrative teams
The candidate will work closely with staff members, research scientists, computational biologists, principal investigators, and external collaborators. Responsibilities may include:
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Contributing to grant applications, progress reports, and scientific proposals
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Supporting manuscript preparation and journal article writing
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Creating publication-quality figures, tables, and data visualizations
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Presenting analyses and findings to interdisciplinary research teams
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Helping translate complex computational results into clear biological and scientific interpretations
Qualifications
Required Education and Experience-
Strong background in both human biology and bioinformatics
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PhD in Computational Biology, Bioinformatics, Data Science, Biostatistics, Systems Biology, Computer Science, or a related field
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Minimum of 2 years of professional experience in a biological, biomedical, or computational research environment
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Strong proficiency in R, Python, and Bash scripting
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Demonstrated experience analyzing biological or biomedical datasets
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Experience developing, implementing, and running bioinformatics workflows
Required Skills-
Strong analytical, mathematical, and creative problem-solving skills
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Excellent written and oral communication skills
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Ability to work both independently and collaboratively in a team-based research environment
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Strong organizational skills and attention to detail
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Ability to prioritize and execute multiple tasks across concurrent projects
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Experience with reproducible data analysis practices and documentation
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Ability to communicate technical results to both computational and non-computational audiences
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Interest in applying large language models, agentic AI, or related computational tools to biomedical research workflows
Preferred Qualifications-
Experience with FDA approval process
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Experience with building apps
Compensation and Benefits-
Salary range: $80,000–$85,000, commensurate with experience
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Full-time, onsite position
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Exciting, collaborative work environment at the forefront of aging research
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Opportunity to work with state-of-the-art technologies and interdisciplinary scientific teams
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Generous benefits package, including:
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Health insurance
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Paid parental leave
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Generous paid time off
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401(k) with 5% employer match
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Work visa sponsorship available for qualified candidates
About the Buck Institute
Our success will ultimately change healthcare. At the Buck Institute for Research on Aging, we aim to end the threat of age-related diseases for this and future generations by bringing together the most capable and passionate scientists from a broad range of disciplines to identify and impede the ways in which we age.
The Buck is an independent, nonprofit institution located in Marin County, California, with the goal of increasing human healthspan, or the healthy years of life. Globally recognized as a pioneer and leader in efforts to target aging — the number one risk factor for diseases including Alzheimer’s disease, Parkinson’s disease, cancer, macular degeneration, heart disease, and diabetes — the Buck seeks to help people live better longer.
We are an equal opportunity employer and strive to create an atmosphere where diversity of identity, experience, and background are welcomed, valued, and supported. Candidates who contribute to this diversity are strongly encouraged to apply.
To Apply
Interested candidates should click the
Apply button to complete the online application.
Please upload both:
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Your CV
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A brief statement of research interests, including the names and contact information for three references.
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