Signal Classification and Anomaly Detection in Contested Spectral Environments
This opportunity supports developing scalable machine learning software that can detect, classify, and flag both known and unknown radio-frequency signals in complex, contested electromagnetic environments. The goal is to outperform human expert SIGINT analysts and integrate the results into multi-function C5ISR decision systems running on commercial off-the-shelf hardware.
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