The Laboratory of Dr. Chaolin Zhang in the Department of Systems Biology, Columbia University Irving Medical Center (CUIMC) has multiple postdoctoral openings to conduct NIH-funded research on mammalian RNA regulatory networks. This posting is to search for candidates in the field of Computational or RNA Systems Biology.
Taking a multidisciplinary approach that tightly integrates biochemistry, molecular biology, genome engineering and high-throughput data analysis and integrative modeling, the Zhang Laboratory studies how RNA and proteins interact to form regulatory networks in the nervous system at the mechanistic and systems levels, how these networks contribute to intrinsic neuronal functional properties, and how such properties are implicated in health and disease. We are working to translate fundamental discoveries to RNA-based precision medicine for devastating disorders with unmet medical needs. The Zhang lab consists of a group of inspired and creative scientists from diverse background. Recent lab members have successfully transitioned into prominent academic and pharmaceutical industry positions. More information about the Zhang laboratory can be found at http://zhanglab.c2b2.columbia.edu.
The candidates will participate in and lead exciting projects that aim to understand fundamental mechanisms of RNA-protein interactions and alternative RNA splicing regulation in normal and disease contexts. Innovative computational and machine learning-based approaches will be used to develop predictive models for analysis of high-throughput genomic data, including large scale bulk/scRNA-seq and CLIP-seq in various cellular contexts, as well as other genomic and genetic variant datasets. The candidates will work in a dynamic environment and also work closely with experimental biologists. Strong mentorship will be provided to help them achieve their career goals.
1. A Ph.D. degree in Computational or Systems Biology, Bioinformatics, Computer Sciences, or related fields.
2. A genuine interest in solving complex biological problems using quantitative approaches.
3. Strong background in statistical modeling and machine learning; experience in genomic analysis using deep neural networks is a plus.
Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the university to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.