Postdoc in evolutionary quantitative genetics of mating systems (Australia)

A postdoctoral position is available to study the evolutionary quantitative genetics of mating systems in a wild bird population. The project would dissect the evolutionary processes that shape mating and breeding systems, and in particular the evolution of mate choice, the dynamics of sexual selection and the interaction of these factors with the social environment. It would involve analyses of data from a long-term study of superb fairy-wrens, a cooperatively-breeding passerine bird with exceptionally high levels of extra-pair paternity. The data-set comprises detailed records on individual life histories, mating patterns, relatedness and population spatial structure. The project provides an exciting opportunity to dissect patterns of variation in breeding success and extra-pair reproduction, and thereby to explore both fundamental evolutionary questions and new theoretical research on indirect genetic effects and inclusive fitness, by combining an exceptional empirical data-set with sophisticated analytical techniques.

The post constitutes an exciting opportunity for a highly-motivated postdoctoral researcher with experience in evolutionary ecology and/or quantitative genetic analyses. It will involve extensive statistical analyses as well as fieldwork at the study site in the Australian National Botanic Gardens. The postdoc will work in collaboration with Loeske Kruuk and Andrew Cockburn to undertake appropriate analyses, but will also have substantial flexibility to pursue their own ideas and approaches. There will be extensive opportunities for further collaboration, high-profile publications, development of technical skills and career development, as well as wider interactions with the active and supportive research environment in the Australian National University's Division of Evolution, Ecology and Genetics.

Applicants should possess (or be nearing completion of) a PhD in a relevant area of evolutionary ecology or genetics. They should have strong skills in complex statistical analyses; in particular, whilst familiarity with quantitative genetic mixed models is by no means essential, it would be a strong advantage. Applicants should also be able to demonstrate excellent writing skills and a strong track record of publication in academic journals. They should be capable of working independently when needed, but must also be a good collaborator with strong interpersonal skills and willingness to assist with supervision and support as required.

For further information, please contact Loeske Kruuk: Email: Loeske.Kruuk@anu.edu.au