Postdoc: bioinformatics of protein innovation and evolvability | all4bioinformatics
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Thursday, 4 April 2013

Postdoc: bioinformatics of protein innovation and evolvability

Postdoc: bioinformatics of protein innovation and evolvability

From the Evolution Directory (EvolDir) via Twitter.


A postdoc position is available to work with Joanna Masel (http://eebweb.arizona.edu/faculty/masel) at the University of Arizona in Tucson. A popular tourist destination surrounded on all four sides by mountainous national and state parks, Tucson is a vibrant city of nearly a million people with an attractive climate.

The Masel group's main research interests are in robustness and evolvability, using a mixture of analytical theory, bioinformatic and simulation approaches. We are looking for someone to do primarily bioinformatic work, but opportunities for related, more theoretical projects (within the Masel group) and/or experimental collaborations (with structural biologist Matt Cordes) also exist. While not an intrinsic part of the primary project, the postdoc training environment will include opportunities to learn the formal methodologies of theoretical population genetics. The EEB department in Tucson was ranked in the top 10 by US News & World Report, and has many other research groups doing evolutionary biology and/or bioinformatics, e.g. those of Mike Sanderson, Ryan Gutenkunst, and Mike Barker, enriching the intellectual environment.

We are looking for someone to investigate the origin of novelty at the protein-sequence level. The conventional view is that new proteins evolve from old proteins via gene duplication and divergence. However, this poses a chicken-and-egg problem, implying an ancient "big bang" of protein creation. This project focuses instead on the ongoing de novo evolution of protein-coding genes from previously non-coding sequences. The postdoc will investigate both case studies of this phenomena, and computational predictors of biochemical properties that might facilitate such conversions over evolutionary timescales. Such predictors will be used to test concrete hypotheses that have arisen from theories of evolvability.

Excellent computer programming skills are strongly preferred, ideally with bioinformatics / genomics experience. Exceptionally strong candidates who come from a more experimental background within evolutionary biology, and who now wish to retrain as bioinformaticians, will also be considered. Experience with (or at least prior interest in) evolutionary biology, protein structure and folding, statistics and other quantitative approaches are all advantages. A start date of August 2013 is preferred but negotiable, and the position is renewable, with funding secured for at least three years.

Contact Joanna Masel at masel@u.arizona.edu for more information or to apply.

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