We are looking for bright, motivated postdoctoral applicants with experience in programming, statistics, genetics and/or behavioral sciences to help us develop methods to elucidate the genetic architecture of complex traits using genome-wide data. This NIH funded work is being conducted at the Institute for Behavioral Genetics (IBG), University of Colorado, Boulder (Matthew Keller, Luke Evans, & Matt Jones) in collaboration with colleagues at the University of Queensland, Australia (Peter Visscher & Jian Yang).
We are developing new methods using imputed or sequenced SNPs in large datasets to gain traction on the importance of rare vs. common variants, genetic heterogeneity, the importance of familial environmental effects, and the degree of non-additive genetic variation underlying complex traits (e.g., see https://www.nature.com/articles/s41588-018-0108-x; additional publications can be found at matthewckeller.com). Minimum qualifications include a Ph.D. in a relevant field, experience with the R statistical language and UNIX (knowledge of C++ or Python is a plus), experience in (or at least a desire to learn) statistical genetics, and a record of scientific productivity.
The position is open for multiyear postdoctoral fellowships to be filled summer of 2018 or after. Interested candidates may contact firstname.lastname@example.org for questions about the position (please attach updated CV), and should formally apply through CU Careers website at the following link: https://cu.taleo.net/careersection/2/jobdetail.ftl?job=13372&lang=en&sns_id=mailto#.WuD2OwePZWo.mailto