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RAP opportunity at Air Force Science and Technology Fellowship Program     AF STFP

Clustering Cislunar and XGEO Regions using Machine Learning Techniques


Space Vehicles Directorate, RV/Space and Planetary Sciences

opportunity location
13.40.01.C0882 Kirtland Air Force Base, NM 871175776


name email phone
Banafsheh Ferdousi 505.846.7218


This opportunity encourages applicants to apply Machine learning techniques to cluster Cislunar regions utilizing the Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon's Interaction with the Sun (ARTHEMIS) dataset. As an ML and Space Physics Specialist, the associate's primary responsibility will be applying expertise in unsupervised learning methods to cluster lunar data. This research gives valuable insights into various Cislunar regions, such as the lunar dayside, lunar wake, Earth's plasmasheet, and magnetic lobes. Evaluate events like the interaction of solar wind with the moon and the effects of solar energetic electrons or protons events, specifically in the context of satellite and moon surface charging. It also provides insight for future lunar exploration missions by identifying regions of interest based on unique features. 

key words
Cislunar, Magnetosphere, Machine learning, artificial intelligence, unsupervised learning, ARTHEMIS, THEMIS, data scientist


Citizenship:  Open to U.S. citizens
Level:  Open to Postdoctoral and Senior applicants


Base Stipend Travel Allotment Supplementation
$95,000.00 $5,000.00

Experience Supplement:
Postdoctoral and Senior Associates will receive an appropriately higher stipend based on the number of years of experience past their PhD.

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