A research position is available in Dr. Vikas Bansal’s lab at the University of California San Diego to work on identifying disease-associated mutations in the human genome using large-scale DNA sequencing datasets. The lab is based in the Division of Genome Information Sciences (Department of Pediatrics) in the School of Medicine and focuses on developing computational methods for the detection of genetic variation using highthroughput DNA sequencing technologies and applying these methods to understand the genetic basis of human disease. The lab has an ongoing project on identifying disease-associated variants in young-onset type 2 diabetes (see recent publications here and here) using large-scale datasets such as the T2D-GENES and UK BioBank, statistical modeling and bioinformatics. A second project aims to leverage novel computational tools for genotyping repetitive sequences in the human genome (see recent publication here) to identify disease-associated variants in regions of the human genome (e.g. duplicated genes) that are typically ignored in standard pipelines. The selected candidate is expected to create/maintain pipelines for processing high-throughput DNA sequencing datasets, analyze both internal and public datasets to extract insights about human disease, and contribute to the preparation of manuscripts. This position is suitable for a postdoctoral researcher or a bioinformatician interested in large-scale data analysis and human genetics.
Relevant recent publications:
Bakhtiari M, Shleizer-Burko S, Gymrek M, Bansal V, Bafna V. Targeted Genotyping of Variable Number Tandem Repeats with adVNTR. Genome Research, October 2018.
Bansal V, Boehm BO, Darvasi A. Identification of a rare missense mutation in the WFS1 gene that causes a mild form of Wolfram syndrome and is associated with risk of type 2 diabetes in Ashkenazi Jewish. Diabetologica, July 2018
Bansal V, Gassenhuber J, Phillips T, et al. Spectrum of mutations in monogenic diabetes genes identified from high-throughput DNA sequencing of 6,888 individuals. BMC Medicine, 2017
Masters or Ph.D. degree in Computer Science, Bioinformatics, Human Genetics or a related field. Candidates with a Bachelor’s degree and several years of experience in Bioinformatics or Human Genetics are also encouraged to apply.
Strong demonstrated competence in programming languages such as Python, R or Matlab
Significant experience working in a Unix/Linux computing environment with large datasets
Proficiency in scientific writing and communication
Significant experience in large-scale data analysis, using bioinformatics tools, and pipeline development
Experience with statistical analysis and data visualization in R
Experience with cloud-based computing
To apply, please send an email to Dr. Vikas Bansal at email@example.com with your CV, contact information for 2-3 references and a brief statement of research experience and interests. More information about the publications and research projects of the lab is available from bansal-lab.github.io