PSInet: data science for climate change research

PSInet is an NSF-funded Research Coordination Network to harness the power of plant water potential (Ψ) and address scientific questions about climate change impacts on earth systems. Prof. Jessica Guo (Hixon/Biology) is seeking 1-2 student data scientists for the Spring 2026, with potential for continuation. Hired students will be full members of the PEPPER (Plant & Ecosystem Physiology, Potential and Environmental Research) Lab, with access to research mentorship and opportunities for conference travel. 

Prof. Guo seeks curious and collaborative data scientists interested in building a reproducible code base and utilizing a database to create data-dense visualizations. Tasks include:
 

  • Understand and shepherd data submissions through the existing cyberinfrastructure (R and Google Drive)
  • Infer causes of failed tests and propose logical fixes
  • Write tidy, sensibly commented code and submit regular PRs
  • Track communication via email, Slack, and GitHub project board
  • Join tables in a database and produce complex visualizations in R

Essay prompt: Please complete this form in lieu of using the URO platform

Name of research group, project, or lab
PEPPER lab
Website
https://psinetrcn.github.io/
Why join this research group or lab?

Plant water potential is a critical driver of water flow and carbon uptake. Though theoretically and practically important, water potential data are difficult to come by due to labor-intensive measurements. PSInet will build the first database of plant water potential in order to spur synthetic research only possible with aggregated and harmonized data, including comparison with coupled climate-vegetation models and validation of remote sensing products. Student data scientists can elect to continue in the PEPPER lab and contribute to PSInet manuscripts. 

Representative publication
Guoetal_2024_NewPhyt.pdf
Logistics Information:
Project categories
Biology
Climate Change
Data Science
Ecology
Environmental Science
Student ranks applicable
First-year
Sophomore
Junior
Student qualifications

Experience in R and git/Hub is helpful, as well as an understanding of biological/ecological experimental design. Example tasks include:

  • understanding data structures and interpreting data errors
  • writing R code to manipulate data using tidyverse
  • creating branches and opening pull requests on GitHub
  • taking initiative to pursue errors, stay organized, and write documentation
  • creating information-dense yet visually-pleasing figures using ggplot

 

Time commitment
Spring - Part Time
Summer - Part Time
Compensation
Paid Research
Number of openings
2
Techniques learned

Students will learn to:

  • work collaboratively in a data science team to advance research objectives
  • understand experimental designs and data structures
  • consider the needs of data contributors and end users
  • become proficient in R coding and project management
Project start
Spring 2026
Contact Information:
Mentor
Jessica Guo
jessicaguo@hmc.edu
Principal Investigator
Name of project director or principal investigator
Jessica Guo
Email address of project director or principal investigator
jessicaguo@hmc.edu
2 sp. | 0 appl.
Hours per week
Spring - Part Time (+1)
Spring - Part TimeSummer - Part Time
Project categories
Ecology (+4)
BiologyClimate ChangeData ScienceEcologyEnvironmental Science