Dana-Farber Cancer Institute Research Fellow in Boston, Massachusetts
The laboratory of Professor Xiaole Shirley Liu (http://liulab.dfci.harvard.edu/) at Dana-Farber Cancer Institute and Harvard T.H.Chan School of Public Health invites applicants for a computational biology postdoctoral position. The research in the laboratory focuses on designing bioinformatics algorithms and integrative genomics approaches to model gene regulation, find novel drug targets and combinations, and predict response to targeted and immunotherapies in cancer. Recently Dr. Liu became the PI of the NCI Cancer Immunologic Data Commons (CIDC) Center to develop the bioinformatics algorithms and infrastructure to integrate comprehensive profiling of all NCI-sponsored immunoncology trials, with the goal of predicting cancer immunotherapy outcomes.
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.
A representative list of recent projects and publications (with Liu Lab as major contributors) include:
Algorithm development: (Zhang et al, Genome Biol 2008; Li et al, Genome Biol 2015; Wang et al, Genome Res 2016; Li et al, Nat Genet 2017; Jiang et al, Cell Systems 2018)
Data integration: (Jiang et al, PNAS 2015; Jiang et al, Nat Genet 2015; Jiang et al, Genome Biol 2015; Zang et al, Nat Comm 2016; Du et al, Nat Comm 2016)
Cancer Epigenetics: (He et al, Nat Genet 2010; Xu et al, Science 2012; He et al, Nat Meth 2014; Liu et al, PNAS 2017; Mei et al, Cancer Res 2017)
CRISPR screens: (Li et al, Genome Biol 2014; Xu et al, Genome Res 2015; Zhu et al, Nat Biotech 2016; Fei et al, PNAS 2017)
Cancer Immunology: (Li et al, Genome Biol 2016; Li et al, Nat Genet 2016; Liu & Mardis, Cell 2017; Li et al, Cancer Res 2017; Pan et al, Science 2018)
In the last decade, 16 trainees from the Liu Lab started tenure track faculty positions, including one Thousand Talents (青千China), two K99 (NIH) and three CPRIT (Texas) awardees.
Ideal applicant should have:
A PhD degree in related field (bioinformatics, physics, statistics, engineering, etc) received in the last 3 years
Strong quantitative background (machine learning, Bayesian inference, etc.) or computational genomics experiences (high throughput sequence analysis, etc.)
Strong programming skills: ((Python | C | C++ | Java) & R)
At least two first authored English papers (or three if co-first authors) with submitted, accepted or published status in journals
Good spoken and written communication skills in English
Interested applicants should submit CV, a letter of interest with a one-page proposal for a project to be conducted in the Liu Lab, and contact of three references..
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.
Job ID: 2018-10952
External Company URL: www.dana-farber.org
Street: 450 Brookline Ave