A postdoctoral position is available in the Department of Genomic Medicine at MD Anderson Cancer Center. We use big data and computational analysis to better understand cancer biology, combined with functional followup and clinical translation. For this specific position we will study glioma evolution using different means, including single cell genomicsand sequencing of patient samples before and after disease progression. We offer a spectacular scientific environment that will suite every ambition. Our lab has recently published papers in Cell (PMID 24120142), Nature (PMID 23792563), Cancer Cell (PMID 20129251), Journal of Clinical Investigation (PMID 23945238) and Genes & Development (PMID 23796897). Other PIs in our Department include Ron Depinho, Lynda Chin and Andy Futreal.
MD Anderson Cancer Center - Making Cancer History
Individuals with training in bioinformatics or computational biology, but also molecular biologists or clinicians with an interest in computational approaches, as well as computer scientists with an interest in biology, are encouraged to apply. The ideal candidate combines experience with (cancer) biology, Unix/Linux and at least one programming language (R, Matlab, Java, Perl, Java, C), and has published (or submitted) at least 2 first author publications in peer reviewed journals (including submitted manuscripts). Salary and benefits are highly competitive and can be negotiated based on experience and background.
MD Anderson Cancer Center is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, gender, sexual orientation, age, religion, disability, or veteran status except where such distinction is required by law. All positions at The University of Texas MD Anderson Cancer Center are security sensitive and subject to examination of criminal history record information. MD Anderson Cancer Center Smoke-free and drug-free environment
A postdoctoral position is available in the Department of Genomic Medicine at MD Anderson Cancer Center. We use big data and computational analysis to better understand cancer biology, combined with functional followup and clinical translation. For this specific position we will study glioma evolution using different means, including single cell genomicsand sequencing of patient samples before and after disease progression.
