Postdoctoral Fellow - Statistical/Computational Genetics : Los Angeles, CA, United States

A postdoctoral research position is immediately available in the Department of Psychiatry and Biobehavioral Sciences at UCLA. The Sul lab is currently seeking passionate postdoctoral research fellows interested in analyzing big genomics data and developing computational and statistical methods to analyze the data. Our lab is involved in a number of large-scale whole-genome sequencing (WGS) projects with several collaborators at UCLA and other institutions such as the Broad Institute and Harvard Medical School. We are especially interested in identifying genetic basis of neurobehavioral disorders such as bipolar disorder, Tourette Syndrome, and schizophrenia. We also participate in the Depression Grand Challenge atUCLA whose aim is to better understand and treat individuals with depression by collecting genome sequences of 100,000 individuals. More information on our past research projects can be found in our lab homepage. Funding is guaranteed for two years and may be renewable. International candidates are welcome to apply for this position.

Job Responsibilities:

• Analyze large-scale whole-genome sequencing, whole-exome sequencing, and microarray data sets for neurobehavioral disorders to identify the genetic basis of the disorders. Our lab currently has access toWGS datasets of hundreds of individuals and will soon analyze WGS of thousands of individuals. This analysis includes variant calling, quality control, imputation, and association analysis.
• Develop statistical/computational methods to better analyze the large-scale genomic data. We are especially interested in developing statistical approaches for next-generation sequencing technologies.
• Participate in collaborations with several institutions. The postdoc will work closely with labs of faculty members in Informatics Center for Neurogenetics and Neurogenomics (ICNN) at UCLA.

Qualifications:

• Ph.D. with research experience in statistical/human genetics, computational biology, bioinformatics, computer science, or a related field
• Experiences in omics data analysis such as whole-genome sequencing, whole-exome sequencing, microarray, or RNA-seq datasets with statistical tools (e.g. GATK, BWA, Picard, VCFTools, PLINK-Seq, PLINK, ShapeIt, Impute2)
• Excellent skills in programming (Java, Python, C/C++, or Perl) and statistical tools ( R ).
• Experience in Linux system and preferably also in high-performance cluster (SGE, LSF).