Job Title: Lead Research Scientist (AI Networking and Security)
Location: University of Texas at Austin
Salary: Negotiable based on experience
Project Affiliation: AI-Driven Networking Solution for C5ISR Applications
About the Project: This exciting opportunity at the University of Texas at Austin involves working on a cutting-edge AI networking project under the guidance of Professor Chandrajit Bajaj. The project focuses on developing Predictive Intelligent Networking (PIN) agents, employing advanced AI techniques for rapid response decision-making in predictive intelligent communication networks. Our innovative approach centers on enhancing network efficiency, reducing overhead traffic, automating PACE communications planning, and improving scalability in challenging environments. Our project is dedicated to crafting advanced machine learning algorithms specifically designed for network optimization and security challenges. Through rigorous real-world simulation scenarios, we aim to deliver robust solutions that excel in environments with incomplete or uncertain data. This role offers the chance to be part of a pioneering effort to create generic solutions for heterogeneous Army networks, working within the confines of existing network protocols.
Key Responsibilities:
- Direct a team of experts to refine network topologies, integrating efficiency and security within AI-driven communication frameworks.
- Architect and implement top-tier security measures, ensuring the integrity and resilience of network systems.
- Oversee the creation and ongoing enhancement of AI agents, driving forward the capability to manage and optimize network functions intelligently.
- Lead the charge in simulation platform development, conducting and supervising rigorous testing and validation to meet and exceed real-world operational demands.
- Harness and further develop cutting-edge machine learning methodologies to surmount network optimization and security hurdles, especially in data-limited or uncertain conditions.
Technical Requirements:
- Expertise in networking and security protocols with a record of practical application in relevant projects.
- Extensive experience with AI/machine learning, particularly within networking contexts.
- Advanced programming proficiency and in-depth experience with network emulation tools such as EMANE.
- Proven track record of leading research initiatives in a methodical, phase-driven project environment.
Preferred Qualifications:
- Ph.D. in Computer Science, Networking, Cybersecurity, or a related discipline.
- Significant experience in research leadership, particularly within military or defense-related projects.
- A deep understanding of PACE Routing, Load Balancing, and Traffic Prioritization, with the ability to innovate and apply these concepts in novel ways.
What We Offer:
- A leading role in a dynamic and collaborative research environment at the University of Texas at Austin.
- The opportunity to lead work on groundbreaking technologies at the forefront of AI and network security.
- Access to leading-edge facilities and resources within the Computer Visualization Lab.
- The chance to make a meaningful impact on critical communications within the defense sector.