Build and iterate RF sensing prototypes for electronic warfare (EW) mapping experiments, including assembling and tuning receive chains (antenna → filtering → LNA/attenuation → SDR) and validating performance through testing.
Execute field-style data collections using SDR platforms (USRP-class preferred), improving measurement reliability and quality through practical iteration (gain staging, front-end behavior, timing and metadata discipline).
Develop DSP workflows on raw I/Q data to detect and characterize signals of interest (time–frequency analysis, correlation/matched filtering, detection metrics, spectral features), with an emphasis on identifying and tracking emitters.
Apply lightweight parameter estimation and modeling to convert measurements into interpretable outputs (e.g., power trends, signal presence probability), and identify failure modes driven by real-world propagation and receiver artifacts.
Create simple, robust data tooling to support experimentation, including repeatable capture → replay → evaluation workflows.
Collaborate closely with senior engineers and researchers to translate ideas into structured experiments, validate assumptions with real data, and clearly document results and lessons learned.
Requirements
Bachelor’s degree (or equivalent experience) in Electrical Engineering, Computer Engineering, Physics, or a closely related field.
Strong hands-on engineering mindset, including comfort building RF setups, swapping components, collecting measurements, and iterating until systems perform as expected.
Foundational knowledge of digital signal processing, including several of the following:
I/Q sampling fundamentals
FFTs and spectrograms (STFT)
basic filtering concepts
correlation and matched filtering
detection fundamentals (thresholding, false alarms, probability of detection)
Prior exposure to SDR systems (coursework, internship, or personal projects), ideally using tools such as UHD, GNU Radio, SoapySDR, or Python-based SDR workflows, including experience capturing and interpreting spectrum and baseband data.
Proficiency in Python (with willingness to work in C++ as needed) for analysis scripts, basic pipelines, and reproducible experimentation.
Self-motivated and adaptable, with the ability to learn quickly, make progress independently, and ask thoughtful questions early.
Tech Stack
Python
Benefits
Top-tier health, dental, vision, short-/long-term disability, and life insurance, with full employee coverage and partial coverage for dependents