Multi-Sensor Tracking Engineer

Johns Hopkins Applied Physics Laboratory•Laurel, MD

13h

About The Position

The Multi-Domain Sensing Architectures and Data Fusion Group at the Johns Hopkins University Applied Physics Laboratory (APL) develops sensing, tracking, and data fusion algorithms and architectures. The Multi-Sensor Tracking Engineer will develop and evaluate algorithms that combine measurements and information from multiple sensing sources, exploiting the strengths of each sensor to provide robust capability in adversarial environments. The group uses research, data analysis, and experimentation to solve difficult sensing and tracking problems. The engineer will develop and evaluate methods for state estimation, data association, track initiation and maintenance, and multi-sensor data fusion. They will 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 on complex tracking applications; and develop analysis packages and briefings for sponsors and other key audiences. APL describes its work environment as supportive, vibrant, and welcoming, with opportunities to grow professionally and build connections with teammates. Its campus is in the Baltimore-Washington metro area. Applications are accepted on a rolling basis.

Requirements

Bachelor of Science in mathematics, electrical engineering, statistics, or a related technical field.
Two 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.
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.
Experience using MATLAB, Python, or similar programming languages to develop algorithms, build simulations, and analyze data.
Ability to obtain an Interim Secret-level security clearance by the start date and ultimately obtain a TS/SCI-level clearance. Eligibility for classified access requires U.S. citizenship and meeting government investigation requirements.

Nice To Haves

Master’s or Ph.D. in applied mathematics, electrical engineering, statistics, or a related technical field.
Active Top Secret security clearance and ability to ultimately obtain a TS/SCI-level clearance. Eligibility for classified access requires U.S. citizenship and meeting government investigation requirements.

Responsibilities

Develop and evaluate 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 to contribute solutions to complex tracking applications.
Develop analysis packages and briefings for sponsors and other key audiences.

Benefits

Robust education assistance program
Retirement plans and contributions
Paid time off
Medical insurance
Dental insurance
Vision insurance
Life insurance
Short-term disability insurance
Long-term disability insurance
Flexible spending accounts
Training and development
Potential sign-on bonus, relocation benefits, locality allowance, or discretionary payments for exceptional performance