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    Postdoc in Metagenomic Data Analysis - New York, United States - Research Foundation at City College of New York

    Research Foundation at City College of New York
    Research Foundation at City College of New York New York, United States

    1 week ago

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    Description
    General Description

    Professors Levi Waldron and project collaborator Nicola Segata (of the University of Trento, Italy), are seeking a motivated and talented scientist with expertise in bioinformatics and/or statistical data analysis to take a central role in the Michael J Fox Foundation ASAP network and the investigation of roles of the microbiome in Parkinson's Disease.

    The position is based at the CUNY Graduate School of Public Health and Health Policy in Harlem, New York City, but remote work is possible.

    The successful candidate will be a key scientist in the MJFF ASAP network and will fill critical roles in project execution including data management and harmonization, curation and meta-analysis of publicly available microbiome data, manuscript preparation, conference presentation, and regular communication with collaborators.

    Authorship on publications will be commensurate with contributions.


    The position offers a competitive salary of $75-$85K/year with health insurance, retirement, and other benefits provided by the Research Foundation of CUNY, travel to one conference annually, and one month per year in the lab of Prof Segata in Trento, Italy, with travel and accommodations paid.

    For any inquiries, please contact Levi Waldron at or Nicola Segata at The position is available immediately and will be filled as soon as possible.

    Other Duties

    The successful candidate will be responsible for data analysis and interpretation, manuscript preparation, and conference presentation.

    They will collaborate with other researchers in the Microbiome Analysis Core facility and the MJFF network, working under the supervision of Prof.

    Nicola Segata (University of Trento) and Prof. Levi Waldron (CUNY), and will have the opportunity to visit the lab of Prof. Segata in Trento, Italy for one month per year.

    Qualifications

    The requirements for this position are a PhD and experience in metagenomic data analysis, but in exceptional cases a candidate without a background in metagenomics can also be considered.

    RFCUNY Benefits
    RFCUNY Employee Benefits and Accruals

    About the Research Foundation

    The Research Foundation of The City University of New York (RFCUNY) was established as a not-for-profit educational corporation chartered by the State of New York in 1963.

    RFCUNY supports CUNY faculty and staff in identifying and obtaining external support (pre-award) from government and private sponsors and is responsible for the administration of all such funded programs (post-award).

    RFCUNY stands between CUNY's principal investigators (PIs) and the sponsors who support them and strives to fulfill its essential responsibilities to both groups.

    Working closely with individual PIs and Grants Officers on the campuses, RFCUNY oversees employment, accounting, audit, reporting, purchasing, and special responsibilities that include management of a planned giving program; liaison with governmental agencies and foundations; negotiation of agreements; facility construction and renovation; protection and commercialization of intellectual property; and compliance with applicable standards in research involving human subjects, animal care, environmental and radiological safety, and conflicts of interest.

    Equal Employment Opportunity Statement

    The Research Foundation of the City University of New York is an Equal Opportunity/Affirmative Action/Americans with Disabilities Act/E-Verify Employer.

    It is the policy of the Research Foundation of CUNY to provide equal employment opportunities free of discrimination based on race, color, age, religion, sex, pregnancy, childbirth, national origin, disability, marital status, veteran status, sexual orientation, gender identity, genetic information, marital status, domestic violence victim status, arrest record, criminal conviction history, or any other protected characteristic under applicable law.

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