Adapting Machine Learning Army Research and Sustainability

About the Research

Data collected from Army research projects and systems testing is varied and often differs from the canonical types of data used to benchmark machine learning (ML) algorithms. In this opportunity, the candidate will evaluate how state-of-the-art ML techniques can be used to extract and predict meaningful information from Army-relevant data. The work will also involve developing novel data preprocessing and analysis strategies with the dual goals of collaborating with the research and testing communities and advancing the applicability of ML to non-canonical domains.

DEVCOM Army Research Laboratory (ARL)

ARL-R-CISD--NCCS

• Dr. Michael Lee, michael.s.lee
  131.civ
• Dr. Brent Kraczek, brent.e.kraczek.civ

• Citizenship: U.S. Citizen Only
• Degree:
  Master’s Degree or Doctoral Degree
• Age:
  Minimum 18 years old
• Disciplines:
  • Chemistry and Materials Sciences (Analytical Chemistry, Bio-inorganic Chemistry, Bio-organic Chemistry, Biophysical Chemistry, Chemistry (General), Environmental Chemistry, Inorganic Chemistry, Materials Sciences, Organic Chemistry, Physical Chemistry, Polymer Chemistry, Theoretical Chemistry)
  • Engineering
  • Mathematics and Statistics
  • Physics
  • Science & Engineering-related fields

ARL-RAP

Questions about this opportunity? Please email ARLFellowship