The Keitt Lab at the University of Texas at Austin announces the immediate 
availability of a 1-year 
postdoctoral position in landscape genetics. We seek an energetic scientist 
interested in utilizing 
genomic, experimental and modeling approaches to understand adaptive dynamics 
across species 
ranges and under environmental change. This opportunity stems from an 
anticipated 1-year 
extension of a 4-year grant funded by NSF. As such, the successful candidate 
will have access to 
extensive genomic, physiological and modeling resources already in place, which 
will facilitate rapid 
progress. Opportunities to participate in renewal and other funding efforts are 
anticipated. 

The ideal candidate will have a strong interest in utilizing genomic tools to 
investigate gene flow and 
local adaptation in landscapes. Relevant areas of expertise may include: 
population genetics, 
genomics, data mining, hierarchical statistical modeling, machine learning, 
GIS, spatial data analysis, 
plant ecophysiology and biogeography. Essential traits are high productivity, a 
willingness to learn, 
and ability to work collaboratively. The successful candidate will be free to 
pursue their own research 
interests as they relate to the funded project.

The position is full time and receives full benefits; salary commensurate with 
experience.

Interested candidates should contact Dr. Timothy Keitt <[email protected]> for 
instructions. 
Applications will be accepted immediately with a starting date no later than 
September 1, 2013.

For more information regarding the Keitt Lab, visit http:/www.keittlab.org/
Original award abstract: http://goo.gl/rKfqR

Related papers:

Lasky, J. R., Des Marais, D. L., McKay, J. K., Richards, J. H., Juenger, T. E., 
& Keitt, T. H. (2012). 
Characterizing genomic variation of Arabidopsis thaliana: the roles of 
geography and climate. 
Molecular ecology, 21(22), 5512–29. doi:10.1111/j.1365-294X.2012.05709.x

Behrman, K. D., Kiniry, J. R., Winchell, M., Juenger, T. E., & Keitt, T. H. 
(2013). Spatial forecasting of 
switchgrass productivity under current and future climate change scenarios. 
Ecological Applications, 
23(1), 73–85.

Kiniry, J. R., Anderson, L. C., Johnson, M. V. V, Behrman, K. D., Brakie, M., 
Burner, D., … others. 
(2013). Perennial Biomass Grasses and the Mason--Dixon Line: Comparative 
Productivity across 
Latitudes in the Southern Great Plains. BioEnergy Research, 1–16.

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