The Yang Lab is seeking self-motivated individuals with strong background of computational biology to study cancer genomics. The main goal of the lab is to explore the functional consequences of somatic alterations in cancer patients, to identify driver alterations, and to understand the evolutionary process of cancer by integrating multi-dimensional data from large scale cancer studies such as The Cancer Genome Atlas (TCGA). The mechanisms of different types of alterations, the functional impact of somatic alterations involving regulatory elements in the human genome, and mechanisms of tumor initiation, progression, metastasis and drug resistance are of particular interest.

　　Responsibilities:

　　The applicant is expected to lead multiple research projects, develop new computational algorithm(s), perform data analysis, collaborate with biologists and physicians, and present/publish the results in scientific conferences/journals. The applicant will have the opportunity to tackle cutting edge problems in biomedical field, interact with world class scientists, and gain experiences and develop skillsets for his/her next career stage.

　　Qualifications:

　　•       Ph.D. in computational biology/bioinformatics/statistics/computer science or related discipline

　　•       Experience in Unix/Linux shell

　　•       Proficient in at least one of the following programming languages: C++, PERL, Python, R, Java

　　•       Experiences with high-throughput sequencing data (WGS, WES, RNA-Seq, ChIP-Seq) analysis

　　•       Excellent oral and written communication skills

　　•       Experiences in one or more of the following fields preferred, but not required: cancer biology, genetics, epigenetics, evolutionary biology, systems biology

　　The position is based in the Ben May Department for Cancer Research and the Institute for Genomics and Systems Biology. To learn more about the PI’s research, please visit http://yanglab.me.

　　The University of Chicago is currently undergoing a major expansion in genomics and computational biology. The Genomic Data Commons (GDC, https://gdc-portal.nci.nih.gov/), ran by the University of Chicago, hosts National Cancer Institute (NCI) funded large scale cancer genomics datasets including TCGA and TARGET as well as the associated clinical data. It provides a unique opportunity to perform large scale data analysis locally. There are also a few large scale computing clusters on campus, including Bionimbus (http://bionimbus.opensciencedatacloud.org/), that the lab has access to for data analysis.

　　To apply, please email your CV, two representative publications, contact information for three references to the PI Dr. Lixing Yang.

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