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Computational Biologist, Stegmaier

Employer
Dana Farber Cancer Institute
Location
Boston, Massachusetts, US
Salary
Competitive
Closing date
May 8, 2021

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Sector
Academic / Research
Field
Informatics / GIS
Discipline
Statistics
Salary Type
Salary
Employment Type
Full time
The Computational Biologist will interact and collaborate closely with other scientists and computational biologists across the Institute and the Broad Institute of Harvard and MIT with the goal of providing necessary computational support to many ongoing projects.

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 tomorrows physician/researchers; we reach out to underserved members of our community; and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.

Responsibilities

Analyze sequencing data, for example from RNAseq and ChIPseq experiments
Deploy existing programs and algorithms to evaluate other experimental data generated in our labs (e.g., drug synergy experiments, chemical screens, CRISPR screens)
Provide support for basic computational tasks in the lab
Document methods for reproducible analysis
Participate in projects to design, build, integrate and maintain software to organize and visualize experimental results, including databases and custom user interfaces
Report data and analytical methods in oral and written formats
Participate in all lab meetings and department meetings at DFCI and Broad Institute

Qualifications

Bachelors degree required. Master's Degree or PhD in Computer Science, Bioinformatics or related field preferred
Familiarity with coding in R or other data analysis / statistics-based language
Familiarity with coding in Python or other similar scripting language
Experience with big data
Experience with data summary visualization
Effective communication skills
Strong organizational techniques, including the ability to handle a variety of tasks in a fast-paced environment
Preferred, but not required:

Experience in computational biology applications
Experience working in a scientific or medical research setting
Experience with pipeline/workflow management frameworks (e.g., Snakemake)
Familiarity with SQL or other database query language

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