Associate Research Scientist

The Columbia University, Robert N. Butler Columbia Aging Center is seeking an Associate Research Scientist to aid in statistical analysis and day-to-day data management associated with multiple concurrent research projects of the Aiello Research Group and Zhang Research Group.

The Aiello Research Group seeks to understand how social and biological factors jointly shape long-term health trajectories. Our research examines the influence of socioeconomic position, stress, epigenetic mechanisms, and biomarkers of infection, immune function, and neurodegeneration on aging-related health outcomes, with a focus on Alzheimer's Disease and related dementias (ADRD). Our ultimate goal is to reduce social disparities in these areas by conducting interdisciplinary, methodologically rigorous research that bridges epidemiology, gerontology, sociology, infectious diseases, immunology, and laboratory science. We strive to produce high-impact, actionable evidence that informs interventions and advances health equity across the life course.

Dr. Zhang's research lies at the intersection of population health, gerontology, biodemography, and economics, focusing on how life course socioeconomic status and participation in social and economic activities contribute to healthy longevity. We use longitudinal cohort studies to investigate how social environments shape life chances for education and work experiences and influence biological health risks, cognitive aging trajectories, dementia risk, and mortality across diverse contexts.

Primary Responsibilities

• Work with the principal investigators, project director, project coordinators, post- and pre-doctoral students, and other collaborators to develop and execute clear, well-documented statistical programs
• Design and implement statistical analysis and data management plans across data types (e.g. laboratory, genetic, qualitative, and quantitative)
• Lead data cleaning and dataset creation for projects in various stages of the research process (e.g., proposal/grant writing, pilot testing, data collection, data analysis, data dissemination, and archived)
• Write statistical-related components (e.g. statistical methods and power analysis sections) for scientific presentations, manuscripts, study protocols, and grant applications; produce tables and figures based on study results
• Provide statistical consultation and advise on model selection
• Review and edit statistical programs and results written by colleagues
• Lead quality assurance and quality control efforts
• Perform data auditing across multiple projects
• Maintain understanding of university data security and sharing policies and securely share datasets with collaborators in accordance with established agreements
• Take initiative to acquire new statistical and/or programming skills as needed

-Appointments are made on a fiscal year basis and are eligible for renewal each July 1st, contingent upon performance and funding

-The search will remain open for at least 30 days after the ad appears and will continue until the position is filled

-Columbia University benefits are offered with this appointment

Required Qualifications

• PhD, ScD or DrPH in social sciences or public health, epidemiology, or related field is preferred
• Experience in measurement and analysis of biological and social variables in the study of health and aging
• Strong interpersonal, leadership, and verbal/written communication skills
• Significant research experience evidenced by peer-reviewed publications
• 5+ years of experience and expertise in measurement and analysis of biological aging, biomarkers, and/or other areas of epidemiology research
• Highly proficient in R, SAS, and/or STATA programming software

Preferred Qualifications

• Demonstrated interest in the research topics investigated by the Aiello and Zhang Research Groups

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.