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 ($17/hr) for the 2024-2025 school year. 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 that can deliver human-generated data as a harmonized database. Tasks include:
 

  • Understand and shepherd data submissions through the existing cyberinfrastructure (R and Google Drive)
  • Infer causes of failed tests and propose logical fixes
  • Track communication via email, Slack, and GitHub project board
  • Build database and add to existing documentation
  • Design and test a Shiny app and R package

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

Name of research group, project, or lab
PEPPER lab
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
Logistics Information:
Project categories
Biology
Climate Change
Data Science
Ecology
Environmental Science
Student ranks applicable
Sophomore
Junior
Senior
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
  • tracking datasets, writing emails, and providing documentation

 

Time commitment
Fall - Part Time
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
Fall 2024
Contact Information:
Mentor
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
Fall - Part Time (+2)
Fall - Part TimeSpring - Part TimeSummer - Part Time
Project categories
Biology (+4)
BiologyClimate ChangeData ScienceEcologyEnvironmental Science