Student Hourly Research Assistant
Position Overview
The EcoFluids Research Group, led by Dr. Amy Hansen, is seeking a student hourly research assistant to work on random forest regression model applied to water quality in a river network. The student will work closely with a postdoctoral researcher and other members of the research group.
Job Description
- 75% Develop and train machine learning models in Python (preprocessing data, creating model, postprocessing and passing output data)
- 25% Communicate with other research group members
Required Qualifications
- Proficiency in Python for machine learning and data analysis
- Experience with machine learning algorithms, particularly random forest regression
- During the semester term of the appointment, the student hourly must be enrolled in no fewer than 6 credit hours. For summer periods the student hourly must: 1) have been enrolled in no less than 6 hours in the past spring semester or 2) be pre-enrolled in upcoming fall semester in no less than 6 hours or 3) be enrolled in summer session or 4) be admitted to study in the upcoming fall semester. Student Hourlies may be undergraduate or graduate students. (Exceptions granted for GRA/GTA/GA appointments DO NOT apply to Student Hourly appointments).
Preferred Qualifications
- Strong problem-solving skills
- Knowledge of hydrology
- Ability to work with geospatial data and tools
- Experience using KU HPC
Additional Candidate Instructions
A complete application consists of the online application, cover letter, and resume. Only complete applications will be considered.
Application review begins 9/6/2024.
Application review begins 9/6/2024.
Contact Information to Applicants
Amy Hansen / amy.hansen@ku.edu
Advertised Salary Range
17.20/hr
Work Schedule
6-10 (academic year), 30 (summer)
Anticipated Start Date
Monday September 16, 2024