The Research Technician Assistant will support research at the intersection of machine learning and environmental economics/policy under Professors Hannah Druckenmiller and Georgia Gkioxari.
Essential duties include training machine learning models, processing large geospatial datasets, implementing quasi-experimental designs, assisting with database building, and contributing to presentations and manuscripts.
Basic qualifications are a bachelor's degree in a quantitative field, experience with machine learning in Python, and good communication skills.
Preferred qualifications include experience with environmental/geospatial datasets, interest in sustainability issues, and prior research assistant experience.
Salary ranges from $19.00 to $30.00 per hour, with comprehensive benefits.
The organization is an equal opportunity employer committed to diversity and accessibility.