Jobs at Buck Institute for Research on Aging

Manages a multi-institution scientific research program focused on proteostasis. Coordinates technical and financial reporting, milestones, compliance obligations, meetings, inventions, agreements, publications, and project risks. Serves as liaison among scientists, principal investigators, funders, technology transfer offices, and partner institutions. Tracks deliverables, amendments, intellectual property disclosures, research assurances, export-control issues, and governance actions while supporting commercialization planning and funder communications.

The Controller leads accounting and finance operations, including financial close, reporting, budgeting, forecasting, grants accounting, payroll, internal controls, and audit compliance. Reporting to the CFO, the role supervises a six-person team, supports Board Finance and Audit Committee matters, partners with organizational leaders, and modernizes finance systems through automation and AI-enabled tools while maintaining strong controls. The position requires expertise in GAAP, Uniform Guidance, nonprofit or grant-funded accounting, and regulatory reporting.

Lead computational analysis for research on intrinsically disordered proteins and regions. Develop reproducible pipelines, integrate HDX-MS, interactomics, cryo-EM, and molecular-dynamics datasets, apply statistical and machine-learning methods, create visualization tools, support experimental design, and collaborate with structural biology, proteomics, and computational modeling teams. Contribute to publications, technical reports, and open computational resources.

Provides comprehensive administrative and executive support to the Chief Scientific Officer, laboratory, Executive Team, and Board of Trustees. Responsibilities include calendar and travel coordination, correspondence, meeting and seminar planning, reimbursements, purchasing, event logistics, recruiting coordination, grant-related support, and office administration. The role requires confidentiality, excellent organization, communication, multitasking, judgment, and proficiency with office, database, graphics, and video conferencing technologies.

Develop and apply advanced AI and machine learning methods to aging biology research. Build computational approaches for large-scale biological and imaging data, including computer vision, segmentation, deep learning, generative AI, diffusion, multimodal, and foundation models. Analyze complex datasets, identify biologically meaningful patterns, collaborate with experimental and computational researchers, and help shape research at the intersection of AI, imaging, and aging.

Develop AI-enabled systems for harmonizing, modeling, and interpreting large biomedical and multi-omics datasets. Build LLM-powered tools, agentic workflows, RAG systems, data pipelines, and predictive models supporting computational biology and aging research. Collaborate with scientists and engineers on data curation, literature mining, annotation, reproducibility, documentation, manuscripts, and research software. Apply machine learning, network analysis, clustering, classification, and biological interpretation to transcriptomics, proteomics, metabolomics, clinical, imaging, and phenotypic data.