We are building a multidisciplinary team to support advanced research and white paper development across key autonomy and sensing domains. This team will target AFRL Research Areas:
The work spans intelligent sensing, embedded AI, sensor fusion, seeker integration, and resilient autonomous behavior under contested conditions.
Minimum: Master’s degree in Computer Science, Electrical Engineering, Aerospace Engineering, Robotics, or a related discipline.
Preferred: Ph.D. or thesis-based Master’s with research in AI/ML, sensor fusion, autonomous navigation, or embedded inference systems.
Ideal Bachelor’s Degrees: Computer Science, Data Science, Electrical Engineering, Aerospace Engineering, Mechatronics.
• 3–10 years of experience in applied AI/ML, embedded systems, or sensor technology development.
• Direct contributions to perception pipelines, sensor hardware design, autonomous platforms, or multi-modal data fusion projects.
• Experience with GNC algorithms, target tracking, or neuromorphic processing preferred.
• Prior R&D for defense applications including seeker systems, AI-enabled target recognition, or GPS-denied navigation.
• Collaboration across hardware/software teams and rapid prototyping environments.
• Deep learning frameworks (PyTorch, TensorFlow) for perception and classification.
• Sensor fusion frameworks (Kalman filters, Bayesian inference, SLAM).
• AI model deployment on embedded platforms using NVIDIA Jetson, Intel Movidius, or custom FPGA/ASIC.
• Signal processing for EO/IR/RF sensors, including FFT, feature extraction, and target tracking.
• High-speed data acquisition and pre-processing techniques (DAQ systems, real-time pipelines).
• Seeker hardware packaging, lens systems, optical sensors, and multimodal integration.
• GN&C algorithms, terminal autonomy, and adversarial robustness modeling.
• Tools: MATLAB, Python (SciPy, NumPy), ROS, OpenCV, Simulink, C++ for real-time embedded development.
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