Announcements of Opportunity
Special Note for SURF@JPL 2024
JPL is operating under a continuing resolution (meaning they are waiting for approval from Congress of NASA's 2024 budget). Additionally, due to other factors, JPL is concerned about a potential budget decrease. This will impact the number of summer internships available. We are working closely with JPL leadership to minimize the impact, but you can expect that AOs will likely not get posted until later this term. To accommodate this later timeline we will offer a second SURF@JPL application deadline. (This extension is for SURF@JPL only.)
- Students who find a JPL mentor early are encouraged to apply by the regular February 22 deadline. For applicants who meet this deadline, awards will be announced on April 1.
- Students who find a JPL mentor later will need to apply by April 19. Awards for this round of applications will be announced on May 6.
Students are also encouraged to apply to the JPL SIP program, which has an application deadline of March 29. For more information about SIP, visit: https://www.jpl.nasa.gov/edu/intern/apply/summer-internship-program
SURF@JPL: Announcements of Opportunity
Announcements of Opportunity are posted by JPL technical staff for the SURF@JPL program. Each AO indicates whether or not it is open to non-Caltech students. If an AO is NOT open to non-Caltech students, please DO NOT contact the mentor.
Announcements of Opportunity are posted as they are received. Please check back regularly for new AO submissions!
**Students applying for JPL projects should complete a SURF@JPL application instead of a "regular" SURF application.
**Students pursuing opportunities at JPL must be U.S. citizens or U.S. permanent residents.
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Project: |
SWOT data analysis using Machine Learning and Cloud Computing
(JPL AO No. 15526)
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Disciplines: | Oceanography, Machine Learning | ||||||||
Mentor: |
Edward Armstrong,
(JPL),
Edward.M.Armstrong@jpl.nasa.gov, |
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Background: | The Surface Water and Ocean Topography (SWOT) mission, a collaborative effort between NASA and CNES (the French space agency), represents a significant advancement in our ability to study the Earth's surface water and oceanography at unprecedented scales. Launched in December 2022, SWOT employed for the first time a Ka-band Radar Interferometer (KaRIn) to measure the height of water surfaces across the globe, including the oceans, lakes, rivers, and reservoirs. This innovative satellite mission aims to provide detailed measurements of sea surface height with a spatial resolution that allows for the observation of fine-scale oceanographic features. Early results have shown stunning low-noise super-high resolution images. We can find something new wherever we look. We welcome motivated students join us to explore this science-rich vast amount SWOT data. | ||||||||
Description: |
We are looking for three to four interns who can cover small-scale oceanography and/or machine learning. The oceanography-related projects require basic knowledge and training in physical oceanography and/or satellite oceanography. The student will analyze the SWOT LR data in 2km and 250m grid to study the ocean circulation and feature at sub-100km scales. The machine learning projects involves working with our team and running/testing existing ML models. Highly-skilled and motivated students are encouraged to conduct new research. We value good work ethics and strong analytical and communication skills. |
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Student Requirements: | Students with the following background are highly encouraged to apply: physical oceanography, remote sensing, geophysical fluid dynamics, deep learning, neural operator, computer vision, physics-informed learning. | ||||||||
Location / Safety: | Project building and/or room locations: . Student will need special safety training: . | ||||||||
Programs: |
This AO can be done under the following programs:
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