Project:	SWOT data analysis using Machine Learning and Cloud Computing (JPL AO No. 15526)
Disciplines:	Oceanography, Machine Learning
Mentor:	Edward Armstrong, (JPL), Edward.M.Armstrong@jpl.nasa.gov, Phone: (818) 393-6710
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.
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:   Program    Available To        SURF@JPL    both Caltech and non-Caltech students  Click on a program name for program info and application requirements.