NRC Research Associate Programs
Fellowships Office
Policy and Global Affairs

Participating Agencies

  sign inOpen Printer View

RAP opportunity at National Institute of Standards and Technology     NIST

Machine Learning for Autonomous Genetic Engineering of Microbial Systems


Material Measurement Laboratory, Materials Measurement Science Division

opportunity location
50.64.31.B8558 Gaithersburg, MD

NIST only participates in the February and August reviews.


name email phone
Aaron Gilad Kusne 301.975.6256


Our project group is working to design and build a machine learning-driven autonomous system for genetic engineering of novel functionality into microbial systems. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position requires expertise in Computer Science, Statistics, or a similar field. Experience with machine learning, genetics, and/or bio-informatics is strongly preferred. 

The postdoc will work together and within a collaborative, interdisciplinary team to enable innovative methods for the predictive engineering of genetic sensors and other living measurement systems in bacteria and yeast. Facilities available for this project include state-of-the-art automation for microbial engineering, culture, and measurement.



key words
Machine Learning; Biology; Bioinformatics; Data Mining; Genetics; Active Learning


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


Base Stipend Travel Allotment Supplementation
$82,764.00 $3,000.00
Copyright © 2024. National Academy of Sciences. All rights reserved.Terms of Use and Privacy Policy