We are seeking a highly motivated candidate, interested in developing and applying innovative statistical and computational methods for translational medicine. The successful candidate will have the opportunity to work on analysis of high-throughput DNA sequencing of tumor and plasma circulating cell-free DNA (cf DNA) with a focus on allele-specific DNA copy number analysis, intratumor heterogeneity and tumor evolution. We are a highly interdisciplinary and interactive group looking for a candidate who shares our passion in employing data science approaches to translational cancer genomics research.
Selected recent publications from our group:
a. Shen R and Seshan V. (2016) FACETS: Fraction and allele-specific copy number estimates from tumor sequencing. Nucleic Acids Res. 44(16):e131
b. Riaz N, Blecua P, Lim RS, Shen R, Higginson DS, Weinhold N, Norton L, Weigelt B, Powell SN, Reis-Filho JS. (2017) Pan-cancer analysis of bi-allelic alterations in homologous recombination DNA repair genes. Nature Communication 8(1):857
c. Zhu B*, Song N*, Shen R*, Arora A, Machiela, MJ, Song L, Landi MT, Ghosh D, Chatterjee N, Baladandayuthapani V and Zhao H. (2017) Integrating Clinical and Multiple Omics Data for Prognostic Assessment across Human Cancers. Nature Scientific Reports, In Press.
d. Martelotto LG, Baslan T, Kendall J, Geyer FC, Burke KA, Spraggon L, Piscuoglio S, Chadalavada K, Nanjangud G, Ng CK, Moody P, D'Italia S, Rodgers L, Cox H, da Cruz Paula A, Stepansky A, Schizas M, Wen HY, King TA, Norton L, Weigelt B, Hicks JB, Reis-Filho JS. (2017) Whole-genome single-cell copy number profiling from formalin-fixed paraffin-embedded samples. Nature Medicine 23(3):376-385
e. Ng CKY, Weigelt B, A'Hern R, Bidard FC, Lemetre C, Swanton C, Shen R, Reis-Filho JS. (2014) Predictive performance of microarray gene signatures: impact of tumor heterogeneity and multiple mechanisms of drug resistance. Cancer Res. 74(11):2946-2961
f. Mo Q, Wang S, Seshan VE, Olshen AB, Schultz N, Sander C, Powers RS, Ladanyi M, and Shen R. (2013) Pattern discovery and cancer gene identification in integrated cancer genomic data. Proc Natl Acad Sci U S A. 110(11):4245-50. PMCID: PMC3600490.
Applicants should hold a PhD degree in bioinformatics, biostatistics, computational biology, or a related field, ideally with experience in NGS sequencing data analysis. The successful candidate should have proficiency in at least one of the statistical programming languages R/Matlab/Python, and possibly one lower level computer language such as C/C++.
The position is available immediately. Please send a copy of your cv and the names of 3 references to Dr. Ronglai Shen at shenr@mskcc.org and Dr. Jorge Reis-Filho at reisfilj@mskcc.org.