Research Assistant for Prof. Julia Kreiner

Opportunity Description:

Position Description: Undergraduate Research Assistant in Ecological Genomics and Machine Learning

The Kreiner Lab at the University of Chicago’s Department of Ecology & Evolution is seeking a motivated undergraduate researcher interested in machine learning, geospatial analyses, and ecological genomics. Our lab investigates how plant populations adapt to human-altered environments, with this project focusing on quantifying patterns of land-use change and its impact on genomic variation. The student will develop and apply convolutional neural network models to identify historical land-use patterns with NASA Landsat imagery, as it relates to genomic change through time, contributing to our understanding of native plant adaptation to increasing agricultural and urban development. This research will either result in a standalone publication, or a contribute to a larger collaborative study in the lab. 

Desired Skills and Experience

• Academic Background: Current undergraduate with coursework in biology, computer science, environmental science, or a related field.
• Computational Skills:
  • Proficiency in Python with a focus on machine learning methods (e.g., building and training neural networks)

  • Experience or familiarity with R for data manipulation and geospatial analysis

  • Exposure to geospatial software (e.g., QGIS) and bioinformatics tools is beneficial but not required
• Analytical Abilities: Demonstrated interest in computational modeling for ecological or biological data, with a focus on real-world applications of machine learning.

• Communication Skills: Willingness to engage in lab discussions, present findings, and collaborate with lab members, with opportunities to showcase work at departmental symposia and conferences.

Application Process: 

Application Form