STR Sensors Division is looking to solve complex radar and RF sensing and counter-sensing challenges for national security-focused clients
Requirements
- Proficiency in one or more scientific or mathematical programming languages, such as MATLAB, Python, and C/C++
- 2+ years of experience in two or more of the following areas: RF/radar signal processing, optimization, waveform design, electronic warfare, machine learning, adaptive signal processing, algorithm development, model & simulation
- Experience with machine learning tasks such as natural language processing, image recognition, semantic segmentation, reinforcement learning, approaches such as Bayesian, deep convolutional and graph neural network methods, and tools such as PyTorch, Ray, TensorFlow/board, and MLflow
- Experience with RF technologies in the defense sector, particularly for sensing and electronic warfare applications including electronic attack, electronic protection, cognitive EW, and advanced ESM techniques and algorithms
Responsibilities
- Design and apply cutting-edge signal processing and machine learning techniques to solve complex radar and RF sensing and counter-sensing challenges
- Work with the team to develop and integrate countermeasures (including algorithm development and signal processing) and evaluate their effectiveness in laboratories, over the air, and on government test ranges
- Design and implement models and simulations for advanced RF systems. Analyze test data and apply results to refine system models
Other
- Ability to obtain an active Secret security clearance, for which U.S. citizenship is required by the U.S. Government
- PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical discipline
- 2-5+ years of relevant experience depending on your degree (BS +5 years, MS +3 years, or PhD)
- Strong mathematical, troubleshooting, written, and verbal communication skills
- Ability to create and present briefings to customers and senior management to provide both high-level and deep technical solution explanations
