Announcements of Opportunity
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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: |
Data-driven Efficient Configuration of Instruments by Scientific Intent for Operational Needs (DECISION)
(JPL AO No. 14113)
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| Disciplines: | Data SCIENTIST , Computer Science | ||||||||
| Mentor: |
Jack Lightholder,
(JPL),
Jack.A.Lightholder@jpl.nasa.gov, |
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| Background: | We are designing a tool to support machine learning applications running onboard future spacecraft. Machine learning systems have many parameters which must be set in order for the system to run optimally. These parameters are traditionally configured during design time for a mission use-case. This is traditionally done by machine learning practitioners. For machine learning systems deployed in the operations environment on spacecraft teams, there can be no one on the team long term to maintain these systems. This would traditionally mean brining back in the machine learning practitioner for any updates. This can slow operations and ultimately results in less updates to the system. We aim to build a system which is easy to use by spacecraft operators to update their machine learning systems. The tool, called DECISION, will take in observation data and use a genetic algorithm running on a supercomputer to find new parameters for the operator. | ||||||||
| Description: | Students will support the development of the DECISION autonomy support tool. Depending on student background, this can be writing machine learning code, developing the UI/UX interface or working on the software framework necessary to get this program to work at scale on AWS/supercomputer. Students will be mentored by a team of machine learning researchers, UI/UX designers and mission operations leaders. | ||||||||
| References: | https://ml.jpl.nasa.gov/ | ||||||||
| Student Requirements: |
- machine learning - high performance computing (AWS/Supercomputing) - front end development / JavaScript |
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| 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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