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 dissect the molecular mechanisms leading to somatic alterations, identify disease-causing events, and understand how the genetic alterations affect treatment response by integrating multi-dimensional data from large-scale cancer studies such as The Cancer Genome Atlas (TCGA). In particular, the applicant will collaborate with physician scientists to study the alterations in patients enrolled in clinical trials of immune checkpoint blockade therapy. The goal is to better predict treatment efficacy based on omic profiles and understand drug-resistant mechanisms.
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.
· 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 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 (firstname.lastname@example.org).