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.
Dr. Heng Li's research group at Dana-Farber Cancer Institute (DFCI) and Harvard Medical School invites applicants for a bioinformatics/computational biology research fellow position. The general research theme is to tackle biological problems with advanced computational and statistical methods. The laboratory develops algorithms fundamental to the application of high-throughout sequence data, including sequence data, including sequence alignment (e.g. bwa and minimap2), sequence assembly (e.g. fermi, miniasm, and wtdbg2), variant calling (e.g. samtools) and data query (e.g. tabix and bgt). The laboratory also studies species and human evolution (Mallick et al, Nature 2016 on SGDP), and analyzes single-cell sequencing data to investigate mutagenesis (e.g. Cheng et al, Science 2017 on the LIANTI protocol), the 3D conformation of genomes (Tan et al, Science 2018 on dip-C) and the mosaicism between cells.
An ideal applicant should have:
Interested applicants should submit a CV, a one-page research proposal, links to past coding projects and three letters of recommendation through the Dana-Farber careers website. The position is available immediately at DFCI in Boston.
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.