Postdoctoral Scholar - Wireless Communications, AI (RL/LLMs), and Software-Defined Radios

We are hiring a Postdoctoral Scholar to join an interdisciplinary research team developing an AI-enabled framework that translates high-level mission objectives into deployable communications signal-processing (DSP) solutions. The role combines (i) strong foundations in digital communications and statistical signal processing with (ii) hands-on implementation using reinforcement learning (including multi-agent RL), large language models (LLMs), and software-defined radio (SDR) testbeds.

You will help build and validate an architecture where specialized communications "agents" collaboratively co-design end-to-end transmit/receive processing chains under formal performance and hardware constraints (e.g., BER, throughput, bandwidth/SEM, latency, and platform budgets).

Responsibilities

1. Communications DSP research & prototyping: develop/benchmark modulation, coding, synchronization, spectral shaping, equalization, and related receiver/transceiver components in simulation and on SDR platforms.
2. AI for communications implementation: implement and experiment with multi-agent reinforcement learning workflows that coordinate component choices and parameters while enforcing system-level feasibility.
3. LLM-assisted engineering workflows: contribute to domain-adapted LLM tools for proposing candidate DSP structures and parameterizations
4. Verification & test automation: validate designs using established tools (e.g., MATLAB, GNU Radio) and develop tests for communications metrics
5. Hardware-aware evaluation (desired): participate in SDR/hardware-in-the-loop experiments and help bridge algorithm design with realistic RF/platform effects.

Required qualifications

1. Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, or related field.
2. Strong background in digital communications / signal processing (e.g., modulation/coding/synchronization; performance evaluation with BER/throughput/bandwidth constraints).
3. Demonstrated experience implementing research software (Python; and/or C/C++) and running simulation studies.
4. Familiarity with modern machine learning tools and techniques
   Preferred qualifications
5. Experience with reinforcement learning, especially multi-agent or distributed/consensus-style coordination.
6. Experience with LLMs for technical tasks (prompting, evaluation, or fine-tuning).
7. Hands-on software-defined radio experience (e.g., GNU Radio, MATLAB toolboxes, USRP-class radios) and/or hardware-in-the-loop validation.

A reasonable estimate for this position is $69,073-$82,836 , based on experience level at time of hire.

Applicants are expected to have a doctoral degree, at the time of hire, in Electrical Engineering, Computer Science or a related field from an accredited university. Qualified candidates should send their curriculum vitae along with the names and address of three references to the following on-line recruitment URL to submit the materials requested.

UC Irvine is part of the premier public university system in the world. UCI is a member of the Association of American Universities (AAU), is ranked as a top-10 public university by U.S. News and World Report, and was identified by the New York Times as No. 1 among U.S. universities that do the most for low-income students. UCI is located in Orange County, four miles from the Pacific Ocean and 45 miles south of Los Angeles. Irvine is one of the safest communities in the U.S. and offers a very pleasant year-round climate, numerous recreational and cultural opportunities, and one of the highest-ranked public-school systems in the nation.

1. Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, or related field.
2. Strong background in digital communications / signal processing (e.g., modulation/coding/synchronization; performance evaluation with BER/throughput/bandwidth constraints).
3. Demonstrated experience implementing research software (Python; and/or C/C++) and running simulation studies.
4. Familiarity with modern machine learning tools and techniques

• 3-5 required (contact information only)

The University of California, Irvine is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC anti-discrimination policy.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
• UC Sexual Violence and Sexual Harassment Policy
• UC Anti-Discrimination Policy for Employees, Students and Third Parties
• 
  APM - 035: Affirmative Action and Nondiscrimination in Employment.
  
  

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.