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Johns Hopkins Applied Physics Laboratory

Not-for-profit UARC delivering national security research

Space Situational Awareness Analyst

Aerospace EngineeringConfirmed live in the last 24 hours
Full-timeLaurel, MD, USAIn-person

About the Job

Requirements

  • An MS or PhD in Applied Mathematics, Aerospace Engineering, Physics, Statistics, Operations Research, Electrical Engineering, Computer Science, or a related quantitative field is required.
  • At least 2 years of professional experience building and testing mathematical models, simulations, or algorithms is required.
  • A background in one or more of estimation theory, Bayesian inference, statistical signal processing, decision theory, optimization, probability and statistics, stochastic processes, or uncertainty quantification is required.
  • Proficiency with Python for analysis, modeling, simulation, and visualization is required.
  • The ability to take an incomplete problem, make reasonable assumptions, run the analysis, and explain both the results and the uncertainty is required.
  • Clear written and verbal communication skills are required.
  • The candidate must be able to obtain a TS/SCI security clearance and meet eligibility requirements for access to classified information, including U.S. citizenship.

Responsibilities

  • Design and run mathematical models and simulations for tracking, estimation, prediction, uncertainty, and decision-making problems.
  • Write Python code to prototype algorithms, evaluate performance, and produce clear technical results.
  • Develop analysis plans for open questions, define metrics, run sensitivity studies, and communicate findings.
  • Test estimation and decision algorithms, validate results, quantify uncertainty, and explain operational impact.
  • Create frameworks that support sensor management, information fusion, and mission planning.
  • Work with experts in astrodynamics, sensing, autonomy, and mission operations.
  • Contribute methods that improve decision support and mission planning under uncertainty.
  • Share results through plots, briefings, short reports, and direct discussion with teams and sponsors.

Desired Qualifications

  • A PhD in a relevant quantitative field is preferred.
  • Experience applying estimation, inference, optimization, or decision analysis to space situational awareness or space domain awareness problems is preferred.
  • Experience with Kalman filtering, nonlinear estimation, multi-target tracking, orbit determination, sensor fusion, sensor management, information theory, optimal control, or partially observable decision processes is preferred.
  • Experience running sensitivity studies, Monte Carlo analyses, trade studies, or algorithm evaluations is preferred.
  • Experience with C++ or MATLAB for scientific computing is preferred.
  • Experience or interest in decision-making methods for autonomous space systems is preferred.
  • Experience presenting analytical results through visualizations, concise writing, and sponsor briefings is preferred.
  • An active Secret clearance or higher is preferred.

About the Company

Johns Hopkins Applied Physics Laboratory

Not-for-profit UARC delivering national security research

Johns Hopkins Applied Physics Laboratory (APL) is a not-for-profit university-affiliated research center that provides solutions to complex national security and scientific challenges through technical expertise, prototyping, research and development, and analysis. It uses engineering, simulations, and studies to design prototypes and deliver analyses that support government and partner organizations. Unlike many commercial firms, APL operates as a non-profit affiliated with Johns Hopkins and focuses on mission-oriented research rather than selling finished products. Its goal is to provide practical, thoroughly tested solutions to public-sector customers by performing research, developing prototypes, and offering expert analysis.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
United States
Founded
1942

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