This project is to develop new techniques required to maximize the extraction of information from SmallSats observations and account for their novel characteristics.  The focus of the research is on adaptive sampling and dynamic uncertainty estimation using both statistical approaches and machine learning methods. 

References:

Christophersen, H., W. Campbell, S. Swadely, et al. (2023). Leveraging SmallSats to improve atmospheric prediction. 103rd AMS, Denver, CO. 

Campbell W., H. Christophersen, L. Satterfield, D. Sidoti. (2023). A strategy for assimilating data from microsats.  ITSC24, Tromso, Norway.

key words

Data assimilation; SmallSats; adaptive sampling; uncertainty quantification; machine learning; verification and validation

Citizenship:  Open to U.S. citizens and permanent residents

Level:  Open to Postdoctoral applicants

Additional Benefits

Relocation

Awardees who reside more than 50 miles from their host laboratory and remain on tenure for at least six months are eligible for paid relocation to within the vicinity of their host laboratory.

Health insurance

A group health insurance program is available to awardees and their qualifying dependents in the United States.