The Breast Oncology Center Computational Biology (BCCB) group is looking for a highly motivated and talented individual with a computational or bioinformatic background to join the Department of Breast Oncology at Dana-Farber Cancer Institute. The candidate for this position will join a team of computational biologists to analyze multi-omic sequencing datasets (DNA, RNA, epigenetic) in the context of multiple clinically oriented studies in order to help advance efforts for translational cancer genomics and precision cancer medicine. The candidate will report to senior scientist staff at the BCCB group and the BCCB leadership (Dr. Rinath Jeselsohn and Dr. Daniel Abravanel).

The Breast Oncology Center Computational Biology group leads the computational biology efforts to characterize multi-omics sequencing datasets that describe the genetic changes that occur across breast cancer. This characterization is done by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain treatment and diagnostic information. The aim of these efforts is to identify genomic alterations and transcriptional changes associated with tumor evolutionary dynamics, mechanisms of resistance, and therapeutic benefit. These datasets and multi-omics associations could help identify novel approaches for personalized care in oncology. In addition, this datasets and association may provide support for new methods in clinical decision-making, biomarkers for rational drug development, and new insights into tumor biology through innovative analyses.

Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.

Minimum Education:
Bachelor's degree required in a STEM field. ÂMaster’s degree preferred in bioinformatics, computational biology, statistics, biostatistics, computer science and/or the life sciences.

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Minimum Experience:
1 year with Bachelor’s degree or 0 years with Master’s degree; academic research experience or authorship in scientific publications experience may substitute for work experience.

KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

• Computational Skills: Knowledge of UNIX/Linux. Familiarity with scripting in Python and statistical programming using R.
• Data analysis Skills: Familiarity with principles of experimental design and the modern data analysis paradigms is required.
• Collaboration: Able to discuss and present results, share ideas accurately and communicate them effectively, both in writing and verbally.
• Strong interpersonal skills – ability to effectively interact with all levels of staff and external contacts.
• Excellent analytical, organizational and time management skills.

At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all, we are equally committed to diversifying our faculty and staff. Cancer knows no boundaries and when it comes to hiring the most dedicated and diverse professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.

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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 characteristics protected by law.

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