Research Associate - Bioinformatics Analyst

Institution/Company:
Harvard T.H. Chan School of Public Health
Location:
Boston, Massachusetts, United States
Job Type:
  • Faculty (Non-tenure track faculty position)
Degree Level Required:
PhD
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Research Associate - Bioinformatics Analyst

About Us
The Harvard Chan Bioinformatics Core (HBC) is a center for bioinformatics research, services and training at the Harvard T.H. Chan School of Public Health. We work closely with biomedical scientists across Harvard to develop innovative approaches for analysis, interpretation, visualization and distribution of scientific discoveries using omic information.HBC projects are a mix of short-and long-term collaborations and HBC researchers include scientists from different disciplines who work with the biomedical research community within the Harvard, MIT and Broad communities, as well as within industry. The HBC emphasizes teamwork and a supportive environment where we learn from each other. This role provides a unique opportunity to participate in exciting and rewarding world-class research that is making a profound impact on human health.

About you
You have a background in biomedical or quantitative science and a strong interest in working with medical and/or biological researchers. You thrive on scientific challenges, and enjoy collaborating with an interdisciplinary team. You can synthesize your knowledge of biology, genetics and cell biology with your computational knowledge to excel at communicating with programmers and wet-lab scientists alike. You are an independent learner, are keen to learn and apply new methods, and are motivated to continually expand your skills. You have good code and data management skills to enable reproducible research and are capable of simultaneously working on different projects and deadlines. You are experienced with next-generation sequencing analysis.

Responsibilities:

The Bioinformatician will support selected research projects, working independently with researchers at the Harvard Chan School, Harvard and the broader Boston biomedical community. They will provide specialized bioinformatic tools and analysis methods to researchers, and collaborate in analyzing and interpreting their data. Tasks will focus on area(s) of expertise in one of the following bioinformatics domains: sequencing (whole genome, exome, bulk RNA, small RNA, single cell RNA, ChIP, methylation, single cell RNA-seq), data integration of multiple data types, functional analysis (enrichment studies, GSEA, networks), or data management and visualization.

Reporting to the HBC director and associate director, and coordinating closely with other Core staff, the applicant will analyze incoming data, and will be required to use existing analytical approaches commonly used in the Core, and assess new methods where appropriate. They will document all work thoroughly, and provide manuscript-level reporting of final analyses and results. The applicant will summarize, analyze and graph data using advanced techniques, and provide direct links to related informatics analysis tools. Other duties will include data management (coordinating with collaborating Research Computing groups and Core developers to ensure consistent data storage), participation in Core and lab meetings and other collaborator meetings around various campuses, and liaising with collaborating researchers. Where appropriate, the applicant may participate in developing manuscripts for publication.

Qualifications:

Basic

  • Master’s or doctoral degree in biological sciences, statistics or related computational field (eg. computational biology or bioinformatics) required
  • scripting abilities (Python familiarity, R proficiency, shell scripting) required
  • working knowledge of biology, genetics and cell biology required
  • experience in at least one of the following next-generation sequencing domains required:
    • Whole genome sequencing
    • Exome-seq
    • Bulk RNA-seq (preferred)
    • Small RNA-seq
    • Single cell RNA-seq (preferred)
    • ChIP-seq
    • Bisulfite-seq

Additional

  • knowledge of functional analysis (enrichment studies, GSEA, networks), data management and visualization
  • proven ability to interpret and analyze large data sets and present results
  • excellent written English and a familiarity with presenting biological results
  • strong interpersonal skills
  • statistical background experience
  • Github or other version control experience
  • ability to produce reproducible code (R Markdown, Latex, Jupyter notebooks, etc)