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    Senior Staff Associate I - New York, United States - HERC: Metro New York & Southern Connecticut

    HERC: Metro New York & Southern Connecticut
    HERC: Metro New York & Southern Connecticut New York, United States

    3 weeks ago

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    Paid Work
    Description

    Employer Name: Columbia University

    The Robert N.

    Butler Columbia Aging Center (CAC) seeks a highly qualified and motived researcher for a Senior Staff Associate I position to participate in the research underway in its Science of Health division.

    The successful candidate will work with a collaborative team of researchers under the direction of Dr. Alan Cohen, Associate Professor of Environmental Health Sciences (in CAC).

    The Cohen lab is interested in understanding how our bodies maintain their internal equilibrium over time, and how loss of this equilibrium contributes to the aging process.

    The lab applies complex systems theory and statistics to epidemiological and clinical biomarker data to understand how the dynamics and ensembles of the markers reveal underlying health status.

    The lab then generates new indices of health that can be used to relate health/aging to lifestyle, psychology, social factors, and environment.

    The Cohen lab takes a multi-disciplinary approach to addressing the science of healthy aging.

    The successful candidate will join this diverse multi-disciplinary team and function as a dry lab manager and data analyst, and as an engaged team member and partner in the science.

    The lab offers excellent working conditions in a collegial and flexible environment, with potential and support for long-term career growth.

    They ensure excellent work-life balance of team members, with potential for flexible hours and some degree of hybrid work.


    Duties:
    Provide statistical analysis of datasets using software such as R or Python. The Senior Staff Associate I will think critically about results and assist with common analysis including correlations, linear/logistic/Poisson regression, multi-level models, survival analysis, principal components analysis, meta-analyses, simulations, and looped analyses to systematically run thousands of permutations on a given analysis Manage a database containing multiple cohort studies that we use for the study, including ensuring data security Data cleaning, manipulation, and troubleshooting, and prepare descriptive analyses Assist in manuscript preparation and perform literature reviews Assist in grant submissions and provide administrative support to the dry lab Correspond with internal and external stakeholders, including funders and collaborating researchers Other duties as assigned

    Minimum Qualifications:
    Bachelor's degree and 6 -10 years' experience in biostatistics, epidemiology, systems biology, demography, economics, or another relevant quantitative/ data analysis field Experience with quantitative data management and analysis Proficiency with statistical software such as R or

    Python Preferred Qualifications:

    Master's degree in biostatistics, epidemiology, systems biology, demography, economics, or another relevant quantitative/ data analysis field Knowledge of relevant subject matter (some combination of aging, physiology, biochemistry, demography, epidemiology, immunology, complex systems theory, ecology, evolutionary biology, anthropology) Database management skills, including knowledge of SQL Ability to write scientific articles or portions of grants independently High-level statistical skills (multi-level models, Bayesian analysis, etc.) Bioinformatics skills Mathematical and computational modeling skills Experience working in an NIH-funded lab Ability to manage social media for the lab, as well as the lab website Ability to bring a new or diverse perspective to the research 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.

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