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

NREL•Golden, CO

46d

About The Position

The Geospatial Data Science (GDS) team within the Strategic Energy Analysis Center at the National Laboratory of the Rockies (NLR) is seeking a 6–12-month intern to support modeling and analysis. The GDS group conducts research at the intersection of energy deployment, big data science, and geospatial modeling and visualization. Our team of researchers develops and applies geospatial algorithms and methods to evaluate the deployment potential for energy technologies, including geothermal, hydropower, transmission, bioenergy, wind, and solar. Geospatial modeling at NLR enables detailed techno-economic assessment, capacity expansion, and power systems modeling of energy resources under a variety of regulatory, sociopolitical, and environmental factors from local to continental scales. The successful intern candidate will support a large and diverse modeling portfolio with activities involving geospatial analyses, literature reviews, cartography, scientific programming, and tasks focused on data preparation, processing, and validation. This position will assist geospatial scientists in developing novel analytical solutions to complex challenges in energy siting, deployment, and adoption. Candidates should be interested in working in an interdisciplinary field, together with geospatial data scientists, software developers, and policy analysts, which will require excellent interpersonal and communication skills.

Requirements

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. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master’s degree and enrolled as PhD student from an accredited institution.
Please Note: Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process. If selected for position, a letter of recommendation will be required as part of the hiring process. Must meet educational requirements prior to employment start date. Must meet educational requirements prior to employment start date.
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

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, NREL’s high-performance computing (HPC) system and the Cloud

Benefits

Benefits include medical, dental, and vision insurance
403(b) Employee Savings Plan with employer match
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.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume