SURF: Announcements of Opportunity
Below are Announcements of Opportunity posted by Caltech faculty and JPL technical staff for the SURF program. Additional AOs for the Amgen Scholars program can be found here.
Specific GROWTH projects being offerred for summer 2019 can be found here.
Each AO indicates whether or not it is open to non-Caltech students. If an AO is NOT open to non-Caltech students, please DO NOT contact the mentor.
Announcements of Opportunity are posted as they are received. Please check back regularly for new AO submissions! Remember: This is just one way that you can go about identifying a suitable project and/or mentor.
Announcements for external summer programs are listed here.
Students pursuing opportunities at JPL must be
U.S. citizens or U.S. permanent residents.
|Project:||Differences in mutation fitness effects between populations|
|Disciplines:||Biology, Computer Science|
Associate Department Head, Molecular and Cellular , (BBE),
|Mentor URL:||http://gutengroup.mcb.arizona.edu (opens in new window)|
NOTE: This project is being offered by a Caltech alum and will be conducted at the University of Arizona in Tucson, AZ.
Understanding natural selection in populations of humans and other species not only reveals the evolutionary past, but also guides efforts to combat genetic and infectious disease. The input of selected genetic variation is quantified by the distribution of fitness effects (DFE) of new mutations, which plays a key role in determining the genetic architecture of human disease and the tempo at which pathogens adapt. Experiments on modest numbers of mutations have shown that fitness effects often differ between populations, but the broad patterns of such differences are unknown. Leveraging the concept of a joint DFE between populations, we are quantifying divergent selection in humans, Drosophila melanogaster, and other species. We hypothesize that the degree of divergent selection will vary dramatically with gene function and with population divergence, offering insight into mechanisms of speciation and local adaptation.
|Description:||The SURF student will apply our joint DFE inference method to a public population genomic data set. Potential data sets include populations of humans, plants, or yeasts. In particular, the student will apply bioinformatics to process the data into suitable form for our software. He or she will then fit models to those data using our custom software. Lastly, he or she will interpret the results with respect to evolutionary and molecular biology.|
Required: Programming experience and basic coursework in molecular genetics
Suggested: Python programming experience, coursework in statistics
This AO can be done under the following programs:
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