The Plant Computational Genomics lab in the Department of Ecology and
Evolutionary Biology at the University of Connecticut seeks motivated PhD
students to join the lab in the Summer/Fall 2019. Our research focuses on
the computational analysis of genomic and transcriptomic data generated by
next-generation sequencing platforms from non-model forest tree species. We
implement this through analysis related to gene finding, gene expression,
transcriptome assembly, and conserved element identification, through
machine learning and computational statistics. We use these methods to
address questions related to genome biology and population genomics. In
addition, we develop web-based applications that integrate BIG data across
domains to facilitate the forest geneticist or ecologist's ability to
analyze, share, and visualize their data (treegenesdb.org). Such
integration requires the implementation of semantic technologies and
ontologies to connect genotype, phenotype, and environmental resources. We
collaborate and contribute to the TRIPAL project (tripal.info).
Potential research topics in our group include 1) development of
visualization tools and integration of high throughout environmental data
to support genome-wide association studies in forest trees; 2) application
of genomic and transcriptomic techniques to evaluate the impact of climate
change on tree populations; 3) development of software solutions to improve
assembly and characterization of non-model plant genomes (and
transcriptomes); 4) interrogation of natural genetic variation across
populations in large, complex conifer genomes; 5) and your ideas here!
Financial support for Ph.D. students is available through research assistantships, teaching assistantships, and university fellowships. Learn more about our active research projects here
Interested candidates should send an email with a research interest statement (1-2 pages), a CV, unofficial undergraduate/graduate transcripts, and GRE scores to Jill Wegrzyn (jill.wegrzyn@uconn.edu). Qualified candidates will be contacted directly for Skype interviews following review. Applications will be reviewed starting December 20th.
For more details on application materials and expectations in the lab, please read the following