24-2024EPSCOR-0019 a.7.4.2 biosignature detection of solar system ocean worlds using science-guided machine learning (sgml)

This $750,000 cooperative agreement, awarded by the National Aeronautics and Space Administration (NASA) Office of STEM Engagement (OSTEM) program (CFDA 43.008), supports research to develop a science-guided machine learning (SGML) approach for detecting potential biosignatures on ocean worlds in our solar system.

The primary awardee, Oklahoma State University, will collaborate with researchers from the University of Tulsa and the University of Oklahoma to conduct experimental and computational investigations of complex geochemical ocean world analogue environments. This interdisciplinary team will create an SGML tool that can accurately classify abiotic versus biotic-containing ocean world samples based on isotope ratio mass spectrometry data, while accounting for differences in geochemical conditions and non-biogenic carbon sources that could confound biosignature predictions. The award period is from August 1, 2024 to July 31, 2027.