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Postdoctoral Fellow, Bioinformatics, Gene Editing, Cancer Biology

Children's National Medical Center
Center for Genetic Medicine Research
United States District of Columbia Washington
https://weililab.org

Description

Computational biology postdoc positions are available in the laboratory of Wei Li, Center for Genetic Medicine Research, Children’s National Medical Center, and Department of Genomics and Precision Medicine, The George Washington School of Medicine and Health Sciences at Washington, DC.


We are devoted to developing cutting-edge computational methods for biology and medicine, with a focus on understanding how coding and non-coding elements function in cancer and childhood diseases. In the past we have developed innovative bioinformatics algorithms to 1) design, analyze and visualize genome-wide CRISPR/Cas9 knockout screening data (MAGeCK/MAGeCK-VISPR, >180 citations, >30,000 downloads); 2) identify genes responsible for cancer drug resistance and synthetic lethal targets (Xiao, Li, et al.) and 3) understand how non-coding elements, especially long non-coding RNAs and enhancers, play roles in cancer (Zhu, Li, et al; Fei, Li, Peng, et al.).


We will conduct research focusing on the following areas: develop algorithms to analyze large-scale screening and sequencing data; use the latest machine learning algorithms to study cancer genomics data and identify predictive biomarkers or drug targets; collaborate with experimental and clinical labs to study a variety of biological and biomedical problems, including glioma and Neurofibromatosis type 1 (NF1); and to study the functions of coding and non-coding elements using genetic screening and single-cell sequencing approaches.


Candidates will join the outstanding research community at Children’s National Medical Center, and George Washington University, and have the opportunity to interact with scientists at nearby institutions including National Institute of Health (NIH), John Hopkins University, University of Maryland, etc. By joining a newly established lab, the candidate will have unique opportunities to set up a research laboratory and interact with the PI/collaborators. The candidate will also gain experiences and guidances in a variety of aspects including grant writing, presentation, career transition, networking, etc.


Children’s National Health System, based in Washington, D.C., has been serving the nation’s children since 1870. Children’s National is #1 for babies, #5 for national children's hospital, and ranked in every specialty evaluated by U.S. News & World Report. Children’s National is one of the nation’s top NIH-funded pediatric institutions. As the capital of United States, Washington DC is the hub of American politics and history. Washington DC metropolitan area (including Virginia and Maryland) is the home of people from diverse backgrounds, and is considered one of the best places to live and work in US. For example, Washington DC is ranked 4th by Business Insider as “Best Places To Live” in US, and many cities in the DC metro area are ranked as “Best Places To Raise A Family”.


Qualifications

Responsibilities of the position will include but not limited to: methodology development, coding, statistical analysis of big biomedical data, writing manuscript, application to postdoctoral fellowship and communication with other researchers. Ideal applicants are expected to have:


-PhD degree in Bioinformatics/Genetics/Computer Science/Statistics or other quantitative science;
-Solid programming skills, strong publication record and the ability to work independently;
-Experienced in cancer genomics data analysis and computational methodology development;
-Ability to communicate and collaborate with other team members;
-Additional expertise in cancer biology, machine learning, single-cell genomics and childhood diseases would be a plus.


Start date

As soon as possible

How to Apply

Candidates should submit a CV, a cover letter of research background and future research goals, and the contact information of three references letters by email to Wei Li. More information can be found on our website (weililab.org).


Contact

Wei Li
li.david.wei@gmail.com