• Dana-Farber Cancer Institute
  • $94,360.00 -141,170.00/year*
  • Boston , MA
  • Scientific Research
  • Full-Time


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.

The Ghobrial Lab in Boston, headed by Dr. Irene Ghobrial, MD, Professor of Medicine is seeking a bright and motivated Computational Biologist to join the team!

The Ghobrial lab ( comprises clinicians and scientists who work on bulk and single-cell sequencing of tumors and their microenvironment (DNA, RNA, protein, epigenetics), as well as liquid biopsy, functional genomics, drug development and computational biology. Our science is conducted in close collaboration with Dr. Ghobrial's clinical team, that is in charge of caring for patients and conducting multiple clinical trials.

Dr. Ghobrial and a team of collaborators have recently received the prestigious Stand Up 2 Cancer Dream Team award ( which will allow us to screen 50,000 individuals at high risk for developing multiple myeloma, in the largest US population study on myeloma precursors to date.


The Computational Biologist will be responsible for developing computational methods to study molecular predictors of disease progression and therapeutic response/resistance in patients with Multiple Myeloma and its precursor conditions, Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma.

The Computational Biologist will have the opportunity to lead projects and submit their work at national conferences, such as the American Society of Hematology (ASH) Annual Meeting and the American Association of Cancer Research (AACR) Annual Meeting.


* Prospective clinical sequencing to guide the care of MGUS and Smoldering Myeloma patients
* Analyzing large sequencing datasets to identify risk factors of disease progression
* Characterizing the increased Myeloma risk in the African/American population
* Studies of resistance to existing and emerging cancer therapies using patient-derived data
* Studies of patient samples for tumor behavior and clinical outcomes
* Studies of cancer immunotherapies to develop predictors of response

You will have hands-on mentorship and collaborations with clinicians, basic and translational scientists (wet and dry lab), working together to improve our understanding of myeloma biology, discover new therapeutic targets, and identify ways to prevent progression from MGUS/SMM to overt myeloma.

Support with MD, PhD or MD/PhD applications will be provided, as needed.


* Bachelors or Masters in a quantitative or computational discipline (e.g. CS, Symbolic Systems, Math, Engineering, Bioinformatics)
* Strong programming skills in Python, R
* Oncology experience a plus
* Strong interest in medicine and improving outcomes for cancer patients
* Excellent communication skills
* Ability to take initiative
* Desire to grow across a broad range of disciplines

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.

Associated topics: biological engineer, biology, biomaterials, biomedical, biophysics, biosynthetic, enzyme, molecular, msat, neuroscience

* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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