Jonathan Flint’s research group at UCLA leverages integrative mouse genetics to study the pathogenesis of mood disorders. The group is looking for post-doctoral bioinformaticians and biostatisticians that would be able to lead an exciting project on the genetic bases of anxiety. This project will identify genes that give insight into a circuit-based understanding of anxiety. Anxiety is a common disorder for which we have relatively ineffective treatments. The project is focused on the development and applications of novel analytical approaches for gene identification in mammal. The team is very interdisciplinary with a focus on quantitative analysis, including statistics, computer science, and mathematical modeling.
Combining novel strategies that the Flint laboratory has pioneered, including the use of outbred rodents for high-resolution genetic mapping, catalogs of genetic variants in mouse strains from genome sequencing, and methods for gene identification, an efficient and simple protocol will be deployed to progress quickly from locus to gene identification. This project will likely lead to new discoveries related to anxiety, but the opportunities in the lab are broader, and our goal is to make an impact on the field of complex traits in mammalian genetics.
Applicants should have the following qualifications:
The position requires a Ph.D. in one of the following fields: computational biology, bioinformatics, biostatistics, human genetics, genomics, computer science, statistics or mathematics. The individual should have a good publication record and show a strong track record in genetics and genomics, as well as good analytical background. The person should be highly motivated, independent, have good verbal and written communication skills, and work well in a highly collaborative and interdisciplinary environment.