NASA Goddard Internship
GEOG Alumni Dr. Mark Carroll is looking for a remote sensing intern at NASA Goddard this Summer. Applications are due March 8th. Anyone with an interest in remote sensing, machine learning, or very high resolution imagery should consider applying!
Title: Deep learning with GPU for image classification of sub 5 m remotely sensed data Type: Internship Session: Summer 2020 Center: Goddard Space Flight Center Description: NASA currently hosts over four Petabytes of very high resolution (VHR) data (< 5 m spatial resolution) in high end computing environments. The fine spatial resolution makes it easier to visually interpret features on the ground but can simultaneously confound traditional image classifiers due to spectral heterogeneity in individual features (i.e. hundreds of pixels in an individual field can look spectrally dissimilar even though they are from the same field). We propose to have a student explore using deep learning approaches in the Advanced Data Analytics Platform (a high-end cloud environment hosted at NASA GSFC with GPU cluster) to improve methods for image classification. The results of this work will provide direct feedback to the PI and will afford the student the opportunity to gain experience with both VHR data and high-end computing. Computer/Software Skills: Linux/unix operating system; Python; exposure to GPU and/or cloud computing a plus but not required; experience with image processing software is a plus Technical Skills: Basic understanding of remote sensing; Basic understanding of machine learning; previous experience with image analysis and image classification a plus Other Skills: good communication skills both verbal and written is important, ability to work well independently and within a team environment are all valuable Academic Level(s): College Junior;College Senior;Master's;Doctorate Major(s): Computer and Information Sciences - Computer Programming; Computer and Information Sciences - Computer Science; Computer and Information Sciences - Data Processing; Multi-disciplinary - Biological and Physical Sciences; Multi-disciplinary
