We seek an energetic and creative candidate, interested in reproducible analysis of biomedical data, for a postdoctoral fellowship position with Dr. Li-Xuan Qin at Memorial Sloan Kettering Cancer Center, New York. This position is to develop and apply statistical methods and software tools for analyzing high-dimensional data such as sequencing, with an emphasis on discerning the role that data preprocessing plays at the interface of method development and application. For example, transcriptomics data normalization may over-compress data variability and subsequently under-estimate the classification error based on cross-validation. In addition, this position offers ample opportunities for multi-disciplinary collaborations with the world’s leading oncology experts and for professional development including publication, presentation at scientific conferences, and involvement in grant writing.
Applicants should hold a PhD degree in biostatistics, statistics, or a related field, ideally with experience in high-dimensional data analysis. The successful candidate should have solid methodological training in statistics, be comfortable working with large data sets, be proficient in R, be organized and meticulous, and have strong verbal and written communication skills.
This position is open immediately until filled. To apply, email a cover letter, CV, and the names of 3 references to Li-Xuan Qin (https://www.mskcc.org/profile/li-xuan-qin) at [email protected], copying Samantha Vasquez at [email protected].