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NRT-IAS Students Participate in Prestigious JGI Summer Internship

February 2, 2021

Although our Bobcat students have been going through an atypical time in regard to their education, UC Merced graduate students Harrison Ho and Jasper Toscani Field have demonstrated that our students are able to succeed in even the oddest of times.

The two students are part of the National Science Foundation (NSF) Research Traineeship (NRT) Intelligent and Adaptive Systems Program (IAS), a program that is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. Within the NRT-IAS program, students work on interdisciplinary group projects to tackle complex data.

Both Ho and Toscani Field participated in an eight-week summer internship with the Joint Genome Institute (JGI). During their internship, the students worked closely with JGI scientists on projects that contribute to projects at the U.S. Department of Energy.

Harrison Ho, second-year Ph.D. student in Quantitative and Systems Biology, learned about the internship through his mentor, Professor Zhong Wang. Ho states that during his internship he “tried to explore codon usage patterns…to see where and why rarely used codons will sometimes appear in highly expressed genes”. Ho and his JGI mentor used a Sequence-to-Sequence Natural Language Processing model, which has been used large and wide to understand the backbone of things such as Google Translate. He states, “[t]here are similarities between the genetic code and human language…and we hope to leverage this technology to help understand genetic patterns.”.

I think the summer project really built upon the things I had learned in my NRT classes”, he states. “It gave me a head start in knowing how to train a machine learning model and how to organize my data to decrease bias in my model”. Ho also mentioned that the NRT focuses on training students to work and communicate effectively in an interdisciplinary team, which he found to be “greatly useful as [he] had to work with many experts in areas [that ranged from] synthetic biology to data science and machine learning”.

“I have not only learned more in-depth scientific knowledge, but also many non-technical strategies to help accomplish a research goal,” he states. “I will try to take this knowledge and apply it to my own Ph.D. research. This internship has deepened my curiosity about how technology can be applied to making scientific discoveries.”

Toscani Field, second-year Quantitative and Systems Biology Ph.D. graduate student, worked on a project, with his JGI mentor, to identify mis-placed taxa (species) within the tree of life using the NCBI taxonomy. This project used “object-oriented programming practices to build a model of the NCBI taxonomy and identified taxa that lower DNA similarity values to an immediate neighbor taxon (like a parent or sibling) than to another taxon in a more distant position in the tree (taxonomy)”.

During his internship, Toscani Field was able to expand and work on his abilities to work with large datasets and improve his object-oriented programming skills. He will implement his skills and expand them further as an NRT fellow.

“I’d like to work at the JGI once I finish my degree at UC Merced”, he states. “Knowing that I was accepted and performed well in such a prestigious internship has been a great motivator during slower parts of my current program at UCM”.


Both students have YouTube videos describing their projects. Links can be found below:

Harrison Ho: 2020 JGI-UC Merced Internship: Applying deep learning to predictive gene expression

Jasper Toscani Field: 2020 JGI-UC Merced Internship: Fixing placements in the taxonomic tree of life