Postdoctoral Position in Computational Genomics

Organization
Institute for Genomic Medicine, Columbia University
Job Location
630 W 168th St
New York, NY 10032
Job Description

A post-doctoral position is available in the group of Dr. Kai Wang (http://wglab.org) at the Institute for Genomic Medicine at Columbia University. Research in the lab focuses on developing genomics and bioinformatics methods to understand the genetic basis of human diseases. The candidate will work on the development of novel statistical approaches to improve power to detect genetic association from sequencing data. The candidate will also apply the algorithms to ongoing large-scale exome/genome sequencing studies on various human diseases and clinical trial populations. The candidate will work in a highly interdisciplinary environment within the Institute for Genomic Medicine and have exposure to a variety of collaborative opportunities. Projects may be tailored to suit the candidate’s research interest and expertise.

Requirements

A suitable candidate should have a doctoral degree in a quantitative field, such as bioinformatics, computational biology, biostatistics or computer science, with strong interest in human genetics. A successful candidate should have sufficient experience in algorithm development, scientific programming, and machine learning. Prior experience with large-scale exome/genome data analysis is preferred.

About Our Organization

The Institute for Genomic Medicine is driving innovation in genomic medicine through cutting-edge research, clinical applications and outreach efforts. Our multi-tiered approach to genomic medicine utilizes large scale genomic sequencing and analysis, paired with functional biology to advance the diagnosis, characterization, and treatment of genetic diseases.   As part of Columbia University's overall Precision Medicine Initiative, we are fully integrated into the research and clinical communities at Columbia University and NewYork-Presbyterian, and will utilize our expertise in genome sequencing, disease biology, and electronic medical records to develop and advance patient-centered precision medicine.

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