Demo

Resilient RF Machine Learning for Dynamic and Novel Emitter Environments

Zintellect
San Antonio, TX Intern
POSTED ON 5/30/2026
AVAILABLE BEFORE 7/30/2026

The Army Research Laboratory (ARL) in San Antonio is seeking a U.S. citizen interested in developing artificial intelligence (AI) and machine learning (ML) for radio frequency (RF) sensing. The ideal candidate will be part of the team that develops new paradigms and technical approaches based on AI/ML that enable learning, adapting, and performing automated detection, classification, modulation recognition, and application intent of complex RF emitters in Multi Domain Operations (MDO) environments.

The candidate will conduct research that seeks to improve the AI/ML solutions for RF applications. Duties include the following:

  • Real-world data driven development of customized, lightweight, scalable algorithms AI/ML for RF applications.
  • Internship will primarily involve algorithm development but may include participation in data collections and field tests.
  • Publish a paper in a peer-reviewed journal.

Advisors:

ARL Advisor:  Dr. D. Marius Necsoiu
ARL Advisor Email: dorel.m.necsoiu.civ@army.mil

 

About ARD

ARL’s Army Research Directorate (ARD) focuses on exploiting concept development, discovery, technology development, and transition of the most promising disruptive science and technology to deliver to the Army fundamentally advantageous science-based capabilities through laboratory’s 11 research competencies. This intramural research directorate also manages the laboratory’s essential research programs, which are flagship research efforts focused on delivering defined outcomes.

About ARL-RAP

The Army Research Laboratory Research Associateship Program (ARL-RAP) is designed to significantly increase the involvement of creative and highly trained scientists and engineers from academia and industry in scientific and technical areas of interest and relevance to the Army. Scientists and Engineers at the CCDC Army Research Laboratory (ARL) help shape and execute the Army's program for meeting the challenge of developing technologies that will support Army forces in meeting future operational needs by pursuing scientific research and technological developments in diverse fields such as: applied mathematics, atmospheric characterization, simulation and human modeling, digital/optical signal processing, nanotechnology, material science and technology, multifunctional technology, combustion processes, propulsion and flight physics, communication and networking, and computational and information sciences. 

About Electromagnetic Spectrum Sciences (ESS)

Novel approaches to sensing and operating across the entire electromagnetic (EM) environment; counter-sensing across the EM spectrum; protection from EM effects; emerging concepts for RF, radars, and electronic warfare (EW).

Questions about this opportunity? Please email ARLFellowship@orau.org.

Hourly Wage Estimation for Resilient RF Machine Learning for Dynamic and Novel Emitter Environments in San Antonio, TX
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