Multi-Sensor Tracking & Data Fusion Engineer

Johns Hopkins Applied Physics Lab; Laurel (MD); On-site; USD 100,000 - 195,000; Full time

Job summary

Johns Hopkins Applied Physics Laboratory (APL) seeks a Multi-Sensor Tracking Engineer to develop and evaluate methods for state estimation, data association, and multi-sensor data fusion across diverse sensing sources. You will run Monte Carlo analyses, build simulations, and deliver design recommendations to sponsor teams.

Ideal candidates hold a BS in a technical field with 2+ years of tracking experience, proficiency in MATLAB/Python, and eligibility for interim Secret clearance with

Qualifications

• Possess a BS in mathematics, electrical engineering, statistics, or related technical field
• Have 2 years of relevant professional experience applying tracking theory, state estimation, statistical estimation, or related methods (relevant doctoral research may be considered in place of professional experience)
• Have experience with one or more tracking topics such as data association, multi-target tracking, Kalman or nonlinear filtering, track initiation and maintenance, or multi-sensor data fusion
• Have experience using MATLAB, Python, or similar programming languages to develop algorithms, build simulations, and analyze data
• Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a TS/SCI level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.
• Have an MS or PhD in applied mathematics, electrical engineering, statistics, or related technical field
• Hold an active Top Secret security clearance, and can ultimately obtain a TS/SCI level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

Responsibilities

• Developing and evaluating methods for state estimation, data association, track initiation and maintenance, and multi-sensor data fusion
• Use Monte Carlo analysis, test data, and quantitative evaluation to characterize algorithm behavior and identify performance limitations
• Conduct studies to develop tracking system design recommendations
• Collaborate with internal and external teams, contributing solutions to complex tracking applications
• Develop analysis packages and briefings for our sponsors and other key audiences

Skills

State estimation

Data association

Multi-target tracking

Kalman or nonlinear filtering

Multi-sensor data fusion

MATLAB

Python

Interim Secret clearance

TS/SCI eligibility

Education

Bachelor's degree in mathematics, electrical engineering, statistics, or related technical field

MS or PhD in applied mathematics, electrical engineering, statistics, or related technical field

Tools

MATLAB

Python

Job description

Johns Hopkins Applied Physics Laboratory (APL) seeks a Multi-Sensor Tracking Engineer to develop and evaluate methods for state estimation, data association, and multi-sensor data fusion across diverse sensing sources. You will run Monte Carlo analyses, build simulations, and deliver design recommendations to sponsor teams.

Ideal candidates hold a BS in a technical field with 2+ years of tracking experience, proficiency in MATLAB/Python, and eligibility for interim Secret clearance with