We are recruiting a talented statistical geneticist/bioinformatician to determine the genetic basis of complex phenotypes in populations descended from known founder individuals. The project uses wheat crop improvement as its focus but the methodologies developed apply to many crops and animals. The BBSRC-funded post centres on the DIVERSE wheat MAGIC population of recombinant inbred lines. These descend from 16 wheat crop varieties grown commercially in the UK, and have been developed primarily to map genes responsible for important agronomic traits. Many users, both academic and from the plant-breeding community will access the project resources.
The post-holder will join the group of Richard Mott at University College London, a dynamic Institute working on quantitative and population genetics across a range of species. The group is affiliated to the Department of Genetics, Evolution and Environment (GEE) and the UCL Genetics Institute (UGI), which offer one of the most exciting work environments in the UK. GEE is a large and collegial Department which embraces essentially all aspects of modern biology and has grown significantly over recent years. The UGI is a vibrant Institute which has been recently created as centre of excellence in medical, statistical and computational genetics.
This post is funded until 31st May 2019 in the first instance and is available now.
Applicants should possess a PhD or equivalent in statistical genetics, bioinformatics or a related subject. Applicants with a strong background in either discipline with the desire and ability to learn new skills are welcome to apply for this position. Previous experience in either quantitative genetic analysis or next-gen sequence analysis, including ability to program in languages such as R, C/C++, Perl, Python, HTML is essential. A research track record e.g. relevant publications in peer-reviewed journals is desirable. Experience with wheat or other plant genetics/genomics is desirable but not essential; we would consider suitably qualified applicants without prior experience with plants.
A Job Description, Person Specification and application form can be accessed at https://goo.gl/hWlq9.
For informal queries on the role please contact Richard Mott r.mott from ucl.ac.uk.
Application deadline 31st March 2016