From Center for Statistical Genetics
Several postdoctoral scientist positions are available at the Center for Statistical Genetics, Department of Neurology, Columbia University, New York, NY.
Postdoctoral research scientist in Mendelian genetics
The candidate is expected to analyzing data for a variety of Mendelian traits with a concentration on the study of nonsyndromic hearing impairment. S/he will work with VCF and BAM files using filtering and bioinformatics approaches. S/he is expected to be able to use a wide variety of analysis tools to analyze sequence data. S/he will also prepare manuscripts and presentations for national and international meetings.
To qualify, the candidate should have a doctoral degree in genetics, bioinformatics, or a degree in a related field.
Please email your curriculum vitae, research statement and the names and contact information for four references to Dr. Isabelle Schrauwen (is2632 [at] columbia.edu) and Dr. Suzanne Leal (sml3 [at] columbia.edu) with the header Mendelian Genetics Postdoc.
Postdoctoral research scientist in statistical genetics
The candidate is expected to work on one or more of the following concentrations:
- Developing statistical methods to analyze complex traits, e.g. approaches to detect pleiotropy and interactions using sequence, imputed, family and population-based data.
- Developing statistical and computational methods for data integration in genetic association studies and functional genomics.
- Analyzing complex traits e.g. late-onset Alzheimer’s disease, age-related hearing impairment, tinnitus, lipids, asthma, type 2 diabetes, and obesity. It includes but not limited to data annotation, quality control, and analysis of sequence, microarray, imputed genotype data, and copy number variations.
- Analyzing multi-omics brain data, e.g., RNA-seq, ATAC-seq, methylation, proteomics, using approaches such as fine-mapping, colocalization and multivariate analysis. Genetic association studies will also be performed at SNP levels (eg molecular QTL mapping) and at gene levels (eg TWAS).
The successful candidate will also write and publish manuscripts and give presentations at international meetings.
Applicants should have a Ph.D. or related degree in computational biology, data science/statistics/biostatistics, bioinformatics, computer science, epidemiology, or other computational related fields. Must have excellent working knowledge in one or more programming languages e.g. R, Python or C/C++. Previous experience analyzing large scale genomic data is highly desirable.
Please email your curriculum vitae, research statement and the names and contact information for four references to Dr. Gao Wang (wang.gao [at] columbia.edu) and Dr. Suzanne Leal (sml3 [at] columbia.edu) with the header Statistical Genetics Postdoc.
Environment and opportunities
The successful candidates will enjoy a dynamic and stimulating research environment in Columbia’s Sergievsky Center on the 168th street campus by the Hudson River, a 20-minute subway ride from mid-town Manhattan. Office area is shared with other interdisciplinary groups focusing on a diverse range of computational, experimental and clinical topics. The candidate will thus benefit from collaboration with world-class scientists, paving the way to a potentially prolific research career.
Faculty at Center for Statistical Genetics are dedicated to training and aiding in career development of trainees. Postdocs will benefit tremendously from the research environment at Columbia Neurology in becoming competitive at various career opportunities, including the K99 Award.