We (NASA/JPL) have postings up looking for interns with strong julia programming skills and knowledge of geospatial data. We need all the help we can get.
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AO #13939: Next-generation tools for Earth Observing analytics in Julia
Background
Over the past decade we have witnessed exponential growth in the volume of Earth observing satellite data that is needed to answer two of society’s most important questions: How has our planet changed in response to human activity and how will it change into the future? To fully utilize the growing archive of data toward answering these questions, the scientific community requires a new suite of tools to fully unlock the knowledge trapped within the data. The Julia general programing language (https://julialang.org/) offers a new paradigm for big-data data science, with mathematical like syntax and C like speed. The language is ideal for deploying machine learning tools for large-scale analysis of massive satellite achieves, allowing us to see the world in new ways. We are looking for interns to join our team and contribute to the building of a new generation of Julia tools and workflows that can help to accelerate our understanding of our home planet.
Description
Successful interns will work closely with Dr. Gardner and his team to develop tools in the Julia programing language for accessing, processing and analyzing massive archives of satellite data. Example datasets include those generated by Dr. Gardner’s ITS_LIVE project (https://its-live.jpl.nasa.gov/), which provides automated, low latency, global glacier flow and elevation change datasets. Depending on the intern’s background, there are also opportunities to help develop and implement machine learning algorithms for generating insights from large data archives of satellite data. All code developed during the internship will be made open source so that it can benefited the greatest number of people.
Desired Number of Participants
4
Background, Skills, Courses
Required Background: Strong programing skills, ideally with knowledge of Julia Beneficial: Knowledge of geospatial data Knowledge of remote sensing principles Experience working in a cloud environment Experience with Git Physics, Math and Engineering background
Web/Literature References
https://julialang.org/ https://juliadatascience.io/ https://its-live.jpl.nasa.gov/
Primary Discipline
Computer Science
Secondary Discipline
Earth Science
Other Discipline
Data Science