Job ID:
Job date: 2018-03-09
End Date:
Company : Children's National Medical Center Country : Role : Postdoc
Job date: 2018-03-09
End Date:
Company : Children's National Medical Center Country : Role : Postdoc
Job 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. What will you get from our lab? Exciting research projects 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); 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:
Additional Info:
How do I apply? Interested 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 (li.david.wei AT gmail) to Wei Li. More information can be found on our website (weililab.org). Job Type: Full-time[Click Here to Access the Original Job Post]
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. What will you get from our lab? Exciting research projects 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); 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 (1) pediatric diseases especially glioma and Neurofibromatosis type 1 (NF1); (2) the functions of coding and non-coding elements using genetic screening and single-cell sequencing approaches; and (3) other exciting collaboration projects.
- Outstanding research and living community
- 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.
Requeriments :
Skills :
Areas :
Additional Info:
How do I apply? Interested 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 (li.david.wei AT gmail) to Wei Li. More information can be found on our website (weililab.org). Job Type: Full-time[Click Here to Access the Original Job Post]