Computational Biologist - Wagle Lab

Dana Farber Cancer Institute
Job Location
Boston, MA 02101
Job Description

Job ID: 27115
Date Posted: 09/18/2015
Location: 450 Brookline Ave
Job Family: Bioinformatics
Full/Part Time: Full-Time
Regular/Temporary: Regular
About Dana-Farber

Located in Boston, 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.


The mission of Dana-Farber Cancer Institute is to provide expert, compassionate care to children and adults with cancer while advancing the understanding, diagnosis, treatment, cure, and prevention of cancer and related diseases.

Our Core Values are:

Impact - Above all else, we make a difference by relieving the burden of disease now and for the future through our research, clinical care, education, outreach and advocacy.

Excellence - We pursue excellence relentlessly and with integrity in all that we do, adhering always to the highest standards of conduct.

Compassion and respect - For those in our care and for one another.

Discovery - We foster the spirit of inquiry, promoting collaboration and innovation across traditional boundaries while celebrating individual creativity.

The Wagle Laboratory at Dana-Farber Cancer Institute/Broad Institute is seeking a COMPUTATIONAL BIOLOGIST to apply and develop computational and statistical methods to analyze whole exome, transcriptome, and single-cell sequencing data for translational and clinical breast cancer research.


The Wagle laboratory focuses on translational cancer genomics and precision (or “personalized”) cancer medicine, using genomic studies to better understanding the mechanisms of therapeutic response and resistance in breast cancer and other solid tumors. The laboratory is based at Dana-Farber Cancer Institute and the Broad Institute of Harvard and MIT, and is a member of the DFCI/Broad/BWH Center for Cancer Precision Medicine. The major goal of the laboratory is to use systematic genomic and molecular characterization of tumor samples from patients with cancer to better understand the molecular determinants of tumorigenesis, characterize mechanisms of therapeutic response and resistance, and identify novel characteristics of tumors that might aid in clinical decision-making.


The candidate will join an interdisciplinary team of computational biologists, bioinformatics analysts, software engineers, experimental biologists and clinical oncologists to develop computational tools and lead the data analysis for several cancer genomics research projects. Specific studies will include the integrated analysis of exome, transcriptome, and single-cell RNASeq from serial tumor biopsies from patients with advanced breast cancer, both before and after targeted treatments, to better understand tumor evolution and mechanisms of resistance to therapies.


The successful candidate will be self-motivated, eager to acquire new knowledge and skills on a regular basis, and must demonstrate critical thinking skills. He or she must be highly organized, motivated, and able to thrive in a fast-paced team science environment. Ability to multi-task, prioritize options, and execute on tasks while anticipating challenges is extremely important.


Specific responsibilities include

  • Actively leading the data analysis for a set of clinical/translational genomics projects in breast cancer.
  • Designing and implementing novel computational and statistical approaches and frameworks to analyze, interpret, and integrate cancer data sets consisting of whole exome, transcriptome, and single-cell RNASeq data.
  • Regularly communicating accomplishments and progress at project team meetings.
  • Participating in genetic interpretation and application of results from cancer genome data.
  • Participating in the preparation of manuscripts for publication, scholarly reports and presents at scientific conferences.
  • Assisting in the mentorship of post-doctoral staff and graduate students.
  • Participating within a team of scientists to foster a culture of scientific excellence.
  • Supervising 1-2 junior analytical staff members.


Job Qualifications

  • A PhD in bioinformatics/computer science or other quantitative field is required.
  • Experience in designing and analyzing experiments using next-generation sequencing technologies is critical. Prior experience in RNASeq analysis is preferred. Previous experience in cancer genomics and breast cancer analysis is a plus.
  • Solid coding skills and experience in algorithm development are critical. Proficiency in R statistical language and Python or Perl is highly desired.
  • Excellent oral and written communication skills and the ability to perform both self-directed and guided research are crucial.
  • The applicant must also demonstrate outstanding personal initiative and the ability to work effectively as part of a team. Ability to meet deadlines and multitask efficiently is a must.


This is a full time, 40 hour per week position.

How to Apply

Please apply directly online at Click Search Job Openings and use the Job ID number to quickly locate the appropriate job listing. Once you have located the desired job, click on the checkbox in the 'Select' column, and then click the 'Apply Now' button, located at the bottom of the screen.

DFCI Employees please apply directly through PeopleSoft Self Service. Sign on to PeopleSoft and navigate to Main Menu > DFCI Careers.

Equal Employment Opportunity

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.


Apply Here



New study finds bias against female lecturers among student course evaluations, the Economist reports.

A research duo finds that science and technology graduate students who turn away from academic careers do so because of changes in their own interests.

Students whose classmates are interested in science are more likely to think about a career in science, technology, engineering, and mathematics, a new study says.

CNBC reports that the genetic counseling field is expected to grow as personalized medicine becomes more common.