Cecile Cres, University of Rhode Island

Project Location

University of Rhode Island-Kingston

SURF Flex eligible?

Yes

Project Description

Metagenomics is a useful technique for probing the functional potentials represented by microbial communities. While the acquisition of metagenomic data can be readily achieved with the development of high-throughput sequencing, the accurate assembly and functional analysis is still a non-trivial task for large datasets. In this project, we plan to apply machine learning tools for the analysis of metagenomic data obtained from a year-round sampling of the Narragansett Bay. Students will gain skills in high-performance computing, data analysis and machine learning. This research will help develop new tools to process and analyze sequencing data and therefore further our understanding of complex environmental microbial communities.

This project involves primarily lab or computer work

Required/Preferred Skills

Prior experience in python programming language. Course preparation in machine learning. Previous experience in deep learning is preferred but not required.

Will students require their own transportation to field sites and/or other off-campus locations?

No