• Research Associate

    University of North Carolina- Chapel Hill (Chapel Hill, NC)


    Employment Type: Permanent Staff (EHRA NF)

     

    Vacancy ID: NF0009337

    Position Summary/Description:

    The UNC -Chapel Hill Metabolomics and Proteomics ( MAP ) Core Facility, housed within the School of Medicine’s Department of Pharmacology, is a University-operated recharge facility that provides state-of-the-art, mass spectrometry- based proteomics and metabolomics services to researchers at UNC and to academic and industry partners across the United States. The facility houses seven Thermo Fisher Scientific instruments dedicated to metabolomics and proteomics applications.

     

    The Research Associate will collaborate closely with members of the MAP Core and external research partners to advance proteomics-based investigations. This role independently leads research initiatives, including protocol development, experimental design, and data interpretation. As a subject matter expert, the Research Associate provides scientific guidance to collaborators, contributes to the planning and execution of complex projects, and ensures the delivery of high-quality, reproducible data. The position requires strong analytical skills, expertise in proteomics methods, and the ability to communicate findings effectively to multidisciplinary teams.

     

    The Research Associate independently leads proteomics research initiatives, including protocol development, experimental design, and data interpretation. The position serves as a subject matter expert, advising collaborators and contributing to strategic decisions in research planning and execution.

    Education and Experience:

    Demonstrated experience in wet lab sample preparation, instrumentation, and/or analysis of -omics datasets.

     

    Familiarity with a range of -omics software platforms, such as Proteome Discoverer, MaxQuant, Spectronaut, and Skyline, is strongly preferred.

     

    Working knowledge of cell biology and standard biochemical sample preparation techniques.

     

    Hands-on experience with LC-MS instrumentation and workflows.

     

    Proficiency in statistical analysis using R or Python, along with bioinformatics expertise, is highly desirable.

    Essential Skills:

    Demonstrated ability to manage multiple projects simultaneously with strong multitasking and time management skills.

     

    Proven capacity to work independently and efficiently in a fast-paced research environment.

     

    Excellent communication and interpersonal skills, with a track record of effective collaboration across diverse teams and laboratories.

    AA/EEO Statement:

    The University is an equal opportunity employer and welcomes all to apply without regard to age, color, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, or sexual orientation. We encourage all qualified applicants to apply, including protected veterans and individuals with disabilities.