NASA internships : Next-generation tools for Earth Observing analytics in Julia

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.

APPLY HERE and search for

AO #13939: Next-generation tools for Earth Observing analytics in Julia


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 ( 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.


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 (, 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


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

Primary Discipline

Computer Science

Secondary Discipline

Earth Science

Other Discipline

Data Science


Uhh! Are there more permanent positions available?

Currently the only permanent job advert at JPL that mentions Julia is for robotics simulations:

I’m hoping that this will change as more people within the organization are exposed to Julia


Can also European PhD students (doing a PhD in Europe, not resident in the US) apply?

@natema I was told years ago that NASA only hires American citizens.

@natema For a paid internship applicants need to reside within the US and must be a student (not necessarily at a US institution). For extremely well qualified applicants there can be travel support. Applicants do not need to be American citizens.


OK, apologies for NASA/JPLs opaque process for applying to an advertisement. I’ve complained but they reassure me that there are no issues with their process (sigh). Here’s some help to navigate the system:

  1. Submit an updated resume and most recent transcript the applicant site here: STEM Internships – NASA Jet Propulsion Laboratory
  2. Candidate must be an enrolled student pursing and undergraduate or graduate level degree with a minimum 3.0 GPA. Candidates that have graduated are not eligible for Education Office internships.
  3. Students must be U.S. Citizens or Permanent Residents living in the US
  4. This internship is being offered through the JPL Year-Round Internship Program
    Once this is done you’ll need to PM me to let me know that your name is in the system
  5. To be successful you will need to demonstrate proficiency in the skills requested in the announcement of opportunity

If you do apply, please PM me to let me know that your name is in the applicant pool, otherwise you can get lost in the system

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