Idaho National Laboratory Internships
Expected Start Date: The program is 10 weeks in duration, starting May 21, 2018. Start date is flexible based on laboratory and candidate availability.
Application Deadline: January 12, 2018
Location: Idaho National Laboratory, Idaho Falls, ID
Salary: Selected candidate will be compensated by either a stipend or salary, and may include one round trip domestic travel to and from the host laboratory. Stipends and salaries will be commensurate with cost of living at the location of the host laboratory. Housing information will be provided to interns prior to arrival at the host laboratory, and will vary from lab to lab.
Earth Modeling Analysis Internship DOE-MSIPP-18-1-INL
The successful candidate will be a current undergraduate or graduate student pursuing a degree in earth and geosciences, GIS, engineering, information systems, or related field.
Desired skills: 3D modeling, Rockswork, Leapfrog search modeling software.
The Idaho National Laboratory is seeking a summer semester intern to perform earth modeling of a field scale research site in support of developing enhance geothermal systems for clean energy production. The intern will work with subsurface scientists to develop geologic earth models of permeability enhancement experiments at the Home Stake Mine in South Dakota. The intern will be expected to create a geologic database for generating 3-D geologic models using RockWorks or Leapfrog earth modeling software. In addition to geologic data, the intern will create input files and database for a variety of geophysical and geoengineering information obtained from numerous continuously cored boreholes into the software to integrate and visualize them for interpretation.
Cyber Security Internship DOE-MSIPP-18-2-INL
The successful candidate will be a current undergraduate or graduate student pursuing a degree in computer science, computer engineering, electrical engineering, power systems engineering, software development, or related field.
Desired skills: Cyber security, computer engineering, computer science, electrical engineering / power systems engineering; software development; physics; statistics; business management; marketing; web development; file management; technical writing; organization.
Idaho National Laboratory's concurrent cooling–Dynamic Line Rating (DLR) methodology is an example of additional data that needs to be effectively integrated into control rooms, and adding forecast (future) data sets to the already complex electric grid operations will require improved - methodic integration and management. The Concurrent Cooling - DLR suite of projects supports the DOE mission to provide high-impact research, development, and demonstration to make clean energy as affordable and convenient as traditional forms of energy by establishing a means to increase the integration of renewable energy generation with the associated increase in transmission line capacity, which are traditionally limited by conductor thermal capacity and can be significantly underutilized. These projects take a science-based approach to advance line rating standards through an innovative methodology. These projects also develop various technology improvements utilizing dynamic, real-time environmental conditions measured and modeled using computational fluid dynamics, leading to average line capacity improvements of 10–40% above static ratings. The weather station data and transmission ampere capacity, or ampacity, calculations comprise an additional layer of data that utilities must react to. Utilities would like to utilize this new capacity to enable additional power flow when the need to transmit power coincides with meteorological conditions (concurrent cooling). Conveying the information to allow the operator to make an informed decision based on this additional information is important to more effective utilization of the transmission asset. Even more important is the timely notification when conditions change in a negative direction as the extra capacity is actively being used. This particular portion of the portfolio of projects aims to look at the cyber security components of advanced data handling and operations within the electric utility industry.
Applied Visualization Internship DOE-MSIPP-18-3-INL
The successful candidate will be a current undergraduate or graduate student pursuing a degree in computer science, computer engineering, mathematics, or related field.
Desired skills: Computer operating systems, systems analysis and design, high performance computing. Experience with C#, C++, Java, Unity 3D.
The intern will complete unique and innovative visualization techniques in the Applied Visualization Laboratory supporting various projects including volume visualization, tele-collaboration techniques, and real-time data visualization & analytics. He/she will be also be exposed to industrial level software development practices and techniques during his assignment. At the completion of the internship, the intern will complete a research paper and poster presentation documenting the completed work.
Synthetic Aperture Radar Internship DOE-MSIPP-18-4-INL
The successful candidate will be a current undergraduate or graduate student pursuing a degree in earth and geosciences, GIS, engineering, or related field.
Desired skills: Experience with GIS software including ArcGIS and ENVI and experience working with both optical and synthetic aperture radar (SAR) data. Experience with geoprocessing and data munging using Python are also highly preferred.
The intern will undertake advanced remote sensing analysis and software development within the Bioenergy Technologies group. Specifically, he/she will conduct a literature review and evaluate the feasibility of the use of Synthetic Aperture Radar (SAR) and other satellite-based sensors for biomass quality characterization at a landscape scale. Based upon literature findings, the intern will utilize cutting-edge software and classification algorithms to perform remote sensing analysis focused on Midwest growing areas. Upon completion, he/she will have developed a remote sensing processing framework and completed a research paper and poster presentation documenting completed work and accomplishments.