Graduate Student

Institution/Company:
University of Connecticut
Location:
Storrs, CT, United States
Job Type:
  • MSc
Degree Level Required:
Bachelor's
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Graduate Student

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 (http://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 (http://tripal.info).

We welcome students from both traditional biology backgrounds as well as more computational ones. Our team is very multi-disciplinary and we collaborate with forest tree biologists around the world.

Responsibilities:

Potential research topics 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 the characterization of non-model plant genomes (and transcriptomes); 4) interrogation of natural genetic variation across populations in large, complex conifer genomes; 5) application of deep learning frameworks to improve genome annotation; 6) investigation of epigenetics in relation to disease resistance in complex genomes; 7) and your ideas here!

Qualifications:

Excellent written and oral communication, as well as strong quantitative skills, are required. Backgrounds in genetics/genomics, evolutionary biology, bioinformatics, and computer science are desired.

  • How to Apply

    Interested candidates should send an email with a research interest statement (~2 pages), a CV/cover letter, unofficial undergraduate/graduate transcripts, and GRE scores to Jill Wegrzyn (jill.wegrzyn@uconn.edu).

Additional Information

Qualified candidates will be contacted directly for Zoom interviews following review. Select candidates will be invited for a campus visit. Applications will be reviewed starting December 20th.

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