PostDoctoral Research Associate

University of Colorado Boulder • Boulder, CO

108d • $65,000 - $70,000

About The Position

We invite applications for a postdoctoral research associate position in the Department of Geography at the University of Colorado Boulder (CU Boulder). The position is supported by a newly funded project aimed at developing advanced computational methods to extract historical geographic information from digital archived maps, and approaches to implement these spatio-temporal data in novel scientific studies of human-environment interactions. This project will extract spatial road network data from historical USGS data originally published between 1884 and 2006 and integrate the extracted spatio-temporal data in research on the impact of transportation infrastructure on urban and economic development and environmental processes. The postdoctoral researcher is expected to collaborate in developing spatially explicit machine learning approaches and/or applying image processing or computer vision techniques to explore innovative ways to understand geographical data and extract useful information from the data. The postdoctoral researcher is expected to lead efforts in data evaluation and demonstrate how the extracted information in combination with other historical data from historical maps or property-level data can be utilized in scientific studies to advance knowledge of human interactions with their environment over extended time periods. The position can start as early as June 2025 or as soon as possible. The initial appointment will be for one year with the possibility of renewal for a second-year contingent on satisfactory performance and fund availability.

Requirements

• PhD degree (or ABD) in Geography/GIScience, Statistics, Computer Science, Information Science or related discipline.
• Expertise in geographic information science, uncertainty assessment, data integration, spatial data extraction, statistical analysis/machine learning.

Nice To Haves

• Strong quantitative backgrounds and programming experience (e.g., Python, R) in statistics, machine learning and spatiotemporal analysis.
• Experience in working with large datasets.

Responsibilities

• Collaborate on machine learning based information extraction from geographic data, develop evaluation processes and perform uncertainty analysis to apply the extracted spatio-temporal data in case studies that model changes in human-environment interactions over long time periods.
• Develop manuscripts for submission to peer-reviewed journals and conference proceedings.
• Present and communicate the findings to the communities of researchers and stakeholders.
• Assist and develop new grant proposals on related topics for submission to funding agencies.
• Mentor graduate and undergraduate students.

Benefits

• Medical insurance
• Dental insurance
• Retirement plan
• Paid time off
• Tuition benefit
• ECO Pass

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Industry: Educational Services
• Education Level: Ph.D. or professional degree