Resilient RF Machine Learning and Novel Emitter Environments

Description

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.

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

• Experience in software programming (Lab View, MATLAB, Python).
• Familiarity with foundational models and self‑supervised learning.
• Experience in real‑world deployment and evaluation of AI systems.
• Expertise in working with large streaming datasets.
• Understanding of computer system design and decentralized systems.
• Hands‑on experience with embedded edge devices, including the deployment of AI algorithms to edge devices.

• Citizenship: U.S. Citizen Only.
• Degree:
  Doctoral Degree required.
• Academic Level(s):
• Doctoral Degree – Postdoctoral Fellow.
• Doctoral Degree – Senior Fellow (5+ years).
• Master’s Degree – Journeyman Fellow.
• Master’s Degree – Senior Fellow (7+ years).
• Bachelor’s Degree – Journeyman Fellow.
• Discipline(s):
  • Computer, Information, and Data Sciences
    • Artificial Intelligence (including Robotics, Computer Vision, Human Language Processing, and Machine Learning)
    • Computer Architecture and Grids
    • Computer Science - Languages and Systems
    • Computer Science - Theoretical Foundations
    • Computer Science (general)
    • Computer Systems Analysis
    • Computer Systems Design (including Signal Processing)
    • Data Science
    • Databases, Information Retrieval, and Web Search
    • Graphics and Visualization
    • Human Computer Interaction
    • Information Science and Technology
    • Information Security and Assurance
    • Networks and Communications
    • Operating Systems and Middleware
    • Scientific Computing and Informatics
    • Software Engineering
  • Engineering
    • Mathematics and Statistics
    • Physics
    • Science & Engineering‑related

Point of Contact: ARL‑RAP. Email: ARLFellowship.