SURF: Announcements of Opportunity
Below are Announcements of Opportunity posted by Caltech faculty and JPL technical staff for the SURF program. Additional AOs for the Amgen Scholars program can be found here.
Specific GROWTH projects being offerred for summer 2019 can be found here.
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! Remember: This is just one way that you can go about identifying a suitable project and/or mentor.
Announcements for external summer programs are listed here.
Students pursuing opportunities at JPL must be
U.S. citizens or U.S. permanent residents.
|Project:||Deep Learning in the Natural Sciences (Astronomy, High-Energy Physics, Oceanography, or Climate Science)|
|Mentor URL:||https://www2.hawaii.edu/~psadow (opens in new window)|
NOTE: This project is being offered by a Caltech alum and will be conducted at University of Hawaii at Manoa.
Rapid progress is being made in machine learning with deep neural networks, and these advances are having a tremendous impact on the natural sciences, where machine learning can help extract knowledge from large data sets. There is a need for machine learning experts to adapt these methods to specific problems in the natural sciences.
|Description:||Student will study the latest deep learning methods (meta-learning, transformer models, Bayesian neural networks) and develop new methods for data analysis in astronomy, physics, or oceanography, in collaboration with University of Hawaii faculty in those respective domains.|
1) Searching for Exotic Particles in High-Energy Physics with Deep Learning, Nature Communications, 5:4308, 2014. http://www.nature.com/articles/ncomms5308
2) Recurrent Inference Machines for Inverse Problems. NeurIPS Workshop on Deep Learning for the Physical Sciences
|Student Requirements:||Experience programming in python. Familiarity with machine learning and statistics. Interest in deep learning.|
This AO can be done under the following programs:
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