PNT Research Engineer

Booz Allen Hamilton•Washington, DC

2d•$62,000 - $141,000•Remote

About The Position

Are you passionate about developing Positioning, Navigation, and Timing (PNT) solutions? Do you enjoy working where science, engineering, and mission-driven innovation meet? If you are excited about supporting cutting-edge science and engineering, and collaborating with multidisciplinary teams focused on strengthening national security and domestic capabilities, this opportunity could be a perfect match for you. As a PNT Research Engineer, you will contribute to the development of innovative, resilient GPS-free navigation platforms. In this position, you will participate in developing comprehensive simulation tools to inform multi-sensor navigation concepts, advancing denoising and sensor-fusion algorithms tailored for selected platforms, and identifying requirements and enhancing the performance of PNT solutions in operational real-world environments. You will collaborate with theoretical and experimental physicists, engineers, aviation and maritime specialists, and cross-disciplinary experts to design advanced navigation solutions. The successful candidate will handle signal processing, programming, and sensor characterization, focusing on adapting algorithms from offline data to real-time airborne and maritime demonstrations.

Requirements

Experience with signal processing, sensor fusion, or navigation
Experience with Kalman filtering, error-state estimation, Bayesian estimation, adaptive filtering, deep learning and reinforcement learning, or machine learning algorithms
Experience with programming languages such as Python, MATLAB, C++, or scientific computing environments
Knowledge of time-series signal processing, including filtering, spectral analysis, noise characterization, correlation analysis, detection, and estimation
Knowledge of geomagnetism, crustal anomalies, Earth-field models, and geomagnetic disturbances
Ability to work collaboratively alongside experts in hardware and software development, prototyping, and deployment
Secret clearance
Master’s degree in Electrical Engineering, Applied Physics, Applied Mathematics, CS, or Systems Engineering

Nice To Haves

Experience with magnetic sensing or autonomous systems
Experience with PNT solutions for contested environments
Experience handling multi-rate sensor data sampled asynchronously
Experience with magnetic anomaly navigation and adaptive compensation techniques
Experience in tactical, navigation, or strategic-grade inertial navigation systems
Experience with map-matching, magnetic map creation, interpolation, or uncertainty analysis
Experience applying machine learning for time-series denoising, anomaly detection, and adaptive compensation
Ability to display peer-reviewed publications in navigation, magnetic sensing, signal processing, autonomous systems, or similar fields
Doctorate degree

Responsibilities

Create a comprehensive simulation platform for magnetic anomaly navigation that incorporates algorithms for denoising, data fusion, and error compensation.
Apply signal processing and filtering methodologies to advance the detection, characterization, and suppression of magnetic interference within a hybrid, multi-sensor framework.
Develop automated routines for heading-error suppression utilizing machine learning and deep learning approaches.
Assist in designing multi-sensor fusion algorithms through Kalman filtering, machine learning, deep learning, or other pertinent techniques.
Aid in the development of autonomous magnetic surveying, uncertainty estimation, change detection, and refresh capabilities.
Design calibration experiments, establish interference characterization protocols, and plan test maneuvers.
Participate in the establishment of quantitative performance metrics for encompassing denoising compensation, map matching, and navigation accuracy.