Location: Boston, MA
Cap-Exempt H-1B Position — No lottery required
Job Ref: JR-4397 Location: 450 Brookline Ave, BOSTON, MA 02215 Category: Fellowships Employment Type: Full time Work Location: Onsite: occasional remote Salary/Pay Rate: $72,000.00 - $76,385.00 per year **Overview** The Jeselsohn Lab and the Breast Oncology Center Computational Biology (BCCB) group is looking for a highly motivated and talented postdoctoral researcher 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 work on multi-omic sequencing datasets (DNA, RNA, epigenetic, spatial transcriptomics and spatial proteomics) in the context of pre-clinical and multiple clinically oriented studies in order to help advance efforts for translational cancer genomics and precision cancer medicine. The candidate will report to the BCCB Director Dr. Rinath Jeselsohn and the BCCB leadership (Dr. Gomez Tejeda Zanudo, Dr. Daniel Abravanel). 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. **OVERVIEW** 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 ing existing and novel computational biology,