Graduate (Year-Round) Intern: Geospatial Data Science Modeling and Analysis

Summary

The National Laboratory of the Rockies is a research laboratory focused on energy systems innovation and geospatial analysis. The intern will support modeling and analysis for energy technology deployment through geospatial data preparation, scientific programming, literature reviews, cartography, and validation. The role involves collaborating with geospatial data scientists, software developers, and policy analysts in distributed computing environments.

Responsibilities

• Manipulating multiple data sources, models, and software tools with scientific and engineering workflows for decision support and data analysis
• Preparing and processing geospatial data using open-source desktop software and programmatic approaches
• Conducting background research on data sets, current modeling approaches, and existing tools
• Developing literature reviews under the guidance of research scientists
• Programming and scripting in Python to conduct analysis and visualize data
• Working in distributed computing environments including internal servers, NLR's high-performance computing (HPC) system and the Cloud

Skills

• Minimum of a 3.0 cumulative grade point average
• Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution
• Post Undergraduate: Earned a bachelor's degree within the past 12 months
• Eligible for an internship period of up to one year
• Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution
• Post Graduate: Earned a master's degree within the past 12 months
• Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution
• Must have completed a bachelor's degree and either: be enrolled in or recently graduated from a master's degree or currently enrolled in a PhD program in fields such as: Geography/GIS, Environmental Science, Computer Science, Engineering, or a related technical field
• To be considered, all candidates must include in their resume and an online code repository such as GitHub with several publicly visible coding projects. Alternatively, please explain in your cover letter why your application does not include a code repository and/or several examples of previous projects
• Demonstrated experience working independently with programming skills in python and libraries such as geopandas, numpy, scipy, shapely, pyproj
• Proficiency and experience with geospatial analysis and modeling techniques using open-source tools, such as QGIS; (please note that ESRI tools are not used in this research group)
• Experience working with geographic transformations and projections
• Ability to work within a dynamically evolving digital environment as a member of collaborative and often-dispersed team
• Critical thinking skills; analytic and research skills; written and verbal communication skills
• Experience with linux/unix
• Experience with collaborative code development
• Experience with Machine Learning
• Experience with the Geospatial data abstraction library (GADL)
• Experience with big geospatial data processing

Qualifications

Must Haves

• Minimum of a 3.0 cumulative grade point average
• Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution
• Post Undergraduate: Earned a bachelor's degree within the past 12 months
• Eligible for an internship period of up to one year
• Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution
• Post Graduate: Earned a master's degree within the past 12 months
• Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution
• Must have completed a bachelor's degree and either: be enrolled in or recently graduated from a master's degree or currently enrolled in a PhD program in fields such as: Geography/GIS, Environmental Science, Computer Science, Engineering, or a related technical field
• To be considered, all candidates must include in their resume and an online code repository such as GitHub with several publicly visible coding projects. Alternatively, please explain in your cover letter why your application does not include a code repository and/or several examples of previous projects
• Demonstrated experience working independently with programming skills in python and libraries such as geopandas, numpy, scipy, shapely, pyproj
• Proficiency and experience with geospatial analysis and modeling techniques using open-source tools, such as QGIS; (please note that ESRI tools are not used in this research group)
• Experience working with geographic transformations and projections
• Ability to work within a dynamically evolving digital environment as a member of collaborative and often-dispersed team
• Critical thinking skills; analytic and research skills; written and verbal communication skills

Nice to Haves

• Experience with linux/unix
• Experience with collaborative code development
• Experience with Machine Learning
• Experience with the Geospatial data abstraction library (GADL)
• Experience with big geospatial data processing

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• 403(b) Employee Savings Plan with employer match, based on eligibility rules
• Sick leave where required by law
• NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement-based awards that include a monetary component
• Some positions may be eligible for relocation expense reimbursement