• Staff Scientist

    Job ID
    Regular Full-Time
    Fred Hutchinson Cancer Research Center
    Biostatistics, Bioinformatics and Computational Biology
  • Overview

    Cures Start Here. At Fred Hutchinson Cancer Research Center, home to three Nobel laureates, interdisciplinary teams of world-renowned scientists seek new and innovative ways to prevent, diagnose and treat cancer, HIV/AIDS and other life-threatening diseases. The Center’s five scientific divisions collaborate to form a unique environment for conducting basic and applied science. Vaccine and Infectious Diseases Division (VIDD), works to eliminate or minimize the impact of globally significant infectious diseases. Within VIDD is the Statistical Center for HIV/AIDS Research & Prevention (SCHARP) which provides statistical support and data management to researchers worldwide in the fight against HIV/AIDS with active studies in the U.S., Africa, Latin America, Asia and Europe. Join us and make a difference! Careers Start Here.

    Biostatistics, Bioinformatics, and Epidemiology (BBE) in the Vaccine and Infectious Disease Division at the Fred Hutchinson Cancer Research Center is seeking a PhD level computational biologist to fill a Staff Scientist position to support the missions of the Vaccine Immunology Statistical Center (VISC) and the Statistical Data Management Center (SDMC) of the HIV Vaccine Trials Network (HVTN).  The primary objective of these Centers is to lead and contribute to study design and analyses related to the development and implementation of innovative statistical and bioinformatics approaches to improve the scientific understanding of immunology, vaccinology, disease-specific biology, and how these components influence vaccine candidates against pathogens of global health significance including HIV, malaria, and TB.  The Staff Scientist will be involved in the analysis of B and T-cell repertoire sequencing data, and participate in multidisciplinary collaborations involving laboratory-based scientists (immunologists, virologists), clinical investigators, biostatisticians, data scientists, and computational biologists.


    • Develop and optimize computational pipelines to enable the integration and management of large and complex data sets
    • Implement computational and statistical tools and algorithms for the preprocessing, analysis, and visualization of pathogen and host sequence data sets
    • Develop well-documented, properly tested, open-source software for reproducible research
    • Interpret results from computational and statistical analysis
    • Assist with study design of pre-clinical and clinical trials
    • Participate in the dissemination of research findings
    • Co-author manuscripts for publication


    • PhD or equivalent degree in bioinformatics, computational biology, biostatistics, statistics, computer science, or a related field.
    • Experience in analysis of next generation sequencing data
    • Excellent programming skills (python, R, C/C++, Java, Github)
    • Excellent interpersonal, oral and written communication skills
    • Strong work ethic
    • Ability to work in a team
    • Ability to manage multiple projects and to meet deadlines
    • Understanding of immunology and virology is a plus

    Our Commitment to Diversity

    We are committed to cultivating a workplace in which diverse perspectives and experiences are welcomed and respected. We are proud to be an Equal Opportunity and VEVRAA Employer. We do not discriminate on the basis of race, color, religion, creed, ancestry, national origin, sex, age, disability, marital or veteran status, sexual orientation, gender identity, political ideology, or membership in any other legally protected class. We are an Affirmative Action employer. We encourage individuals with diverse backgrounds to apply and desire priority referrals of protected veterans. If due to a disability you need assistance/and or a reasonable accommodation during the application or recruiting process, please send a request to our Employee Services Center at escmail@fredhutch.org or by calling 206-667-4700.


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