Senior Research Scientist - Network Systems

• Strong foundation in RF communications theory, including modulation/demodulation, propagation, link budgets, and spectrum analysis
• Hands-on experience with digital signal processing (DSP) — filtering, FFT/spectral analysis, detection, estimation, and adaptive algorithms
• Demonstrated expertise in compressive sensing, including sparse signal recovery, L1/L2 optimization, sensing matrix design, and sub-Nyquist sampling techniques

• Proficiency designing and implementing ML algorithms (supervised, unsupervised, deep learning, reinforcement learning) with emphasis on signal/time-series data
• Experience building end-to-end ML pipelines — data ingestion, preprocessing, feature engineering, training, validation, deployment, and monitoring
• Knowledge of ML architectures including CNNs, RNNs/LSTMs, transformers, autoencoders, and GANs, with applied experience selecting the right model for RF/signal and data analytic problems
• Strong data analytics skills: exploratory analysis, statistical modeling, visualization, and deriving actionable insight from large/complex datasets
• Hands-on with frameworks such as PyTorch, Tensor Flow/Keras, scikit-learn, and data tooling (Num Py, pandas, Spark)
• Experience with MLOps practices — version control, containerization (Docker), CI/CD, experiment tracking (MLflow, W&B), and model serving

• Strong programming skills in Python and C/C++; MATLAB a plus
• Version control (Git), Linux development environment, and scripting proficiency

• BS in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, or related discipline and a minimum of 12 years of experience;
  Minimum of 10 years with MS/MA;
  Minimum of 7 years with Ph.D.
• Demonstrated project or publication record spanning both RF/signal processing and machine learning domains
• US Citizenship

• Experience applying ML to RF problems: signal classification, spectrum sensing, RFI mitigation, cognitive radio, direction finding, or emitter identification
• Background in DoD / IC programs, EW, SIGINT, or radar systems
• Active security clearance (or ability to get one)

• Clear technical communication — able to translate algorithms to implementation and results to stakeholders, and write technical papers and reports
• Self-directed, with experience taking prototypes from concept through demonstration

Peraton Labs delivers innovative solutions and revolutionary new capabilities to solve the most difficult and complex challenges for government agencies, utilities, and commercial customers. With a distinguished heritage tracing back to Bell Labs, Bellcore, and Telcordia, our experts pave the way. Peraton Labs' cybersecurity and network research protects mission-critical systems and national cyber infrastructure and efficiently utilizes spectrum and system resources by employing technologies in the areas of computer network defense, secure-by-design, AI/ML and deterministic and stochastic optimization.

Our projects span several areas of interest. Our core competencies include (but are not limited to):

• Networking and wireless research including 5G and non-terrestrial networks
• Cyber Security including formal methods, side channel analysis, high-fidelity emulation of cyber physical systems (CPS)
• Resilient networking in support of cyber mission goals
• Software-defined networking for cyber defense and deception
• Artificial intelligence (reasoning, probabilistic inference, machine learning)