• Research Fellow

    Location US-MA-Boston
    Job Posted Date 1 month ago(9/11/2019 12:12 PM)
    Job ID
    2019-16664
    Category
    Fellowships
    Type
    full time
    Grade
    41
  • Overview

    Located in Boston and the surrounding communities, Dana-Farber Cancer Institute brings together world renowned clinicians, innovative researchers and dedicated professionals, allies in the common mission of conquering cancer, HIV/AIDS and related diseases. Combining extremely talented people with the best technologies in a genuinely positive environment, we provide compassionate and comprehensive care to patients of all ages; we conduct research that advances treatment; we educate tomorrow's physician/researchers; we reach out to underserved members of our community; and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.

     

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    JOB TITLE: Postdoctoral Fellow (computational)

     

    DEPARTMENT: Dana-Farber Cancer Institute/Medical Oncology

     

    GENERAL SUMMARY:

    Dr. Marios Giannakis at the Dana-Farber Cancer Institute (with co-affiliation at the Broad Institute of MIT and Harvard) is seeking a highly motivated, exceptional candidate to join his laboratory towards obtaining novel insights for the molecular epidemiology, treatment and associated response and resistance of colorectal cancer through the computational analysis of large-scale datasets. The successful candidate will independently lead projects integrating molecular, pathologic and clinical data as well as collaborate with a diverse array of community members both at the Dana-Farber Cancer Institute and the Broad Institute of MIT and Harvard. This individual will work towards analyzing some of the world’s most comprehensive and well-annotated biomedical datasets and develop novel computational approaches towards tackling several of the most pressing questions in cancer biology today. Consequently, there is unparalleled potential for your contributions to be published, used and recognized worldwide.

    Responsibilities

     

    PRIMARY DUTIES AND RESPONSIBILITIES:

    1. Independently lead and conduct computational biology and genomic research projects.
    2. Analyze large-scale biomedical data such as whole-exome and whole-genome sequencing, single-cell and bulk RNASeq data, functional genomic, microbiomic, metabolomic and other multi-dimensional datasets
    3. Utilize and develop computational tools for the analysis and integration of complex datasets
    4. Conceive, implement and test statistical models
    5. Write manuscripts, present and publish impactful research
    6. Work together with experimental biologists to design experiments and analyze resulting data

    KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

    1. Knowledge and experience with a wide range of biological databases and resources, such as TCGA, GenBank, EnsEMBL, the UCSC genome browser, and others.
    2. Strong statistical knowledge and programming using languages such as R, Python, Perl, MATLAB, Java R and related tools, as well as ability to prototype software solutions for data analysis.
    3. Strong background and publication record in computational biology, bioinformatics or other quantitative principles
    4. Excellent interpersonal and communication skills are essential

     

    Qualifications

    MINIMUM JOB QUALIFICATIONS:

    PhD in Bioinformatics, Computer Science, Statistics, Life Sciences or any quantitative discipline

     

    Please submit your CV, cover letter, and three references. In your cover letter please outline your research interests, how they intersect with those of our laboratory and what you hope get out of your postdoctoral training. In addition, describe how your background may synergize with the strengths of our laboratory/work and any plans for obtaining independent funding.

     

    Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other groups as protected by law.

     

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