Sensor Signal Processing Engineer at Johns Hopkins Applied Physics Laboratory (APL)

We are seeking an experienced engineer to help us design and develop concepts and algorithms that will solve complex sensor and source integration and data association challenges in networked sensor systems. As a member of our team, you will contribute to the development of the Navy's next generation of networked sensor systems that will ingest, associate, and fuse dissimilar information, ranging from active and passive sensor positional measurements to external source tracks and target characterization attributes, to provide an accurate, common, and actionable composite track picture across all platforms in support of distributed warfare concepts.

As a Sensor Signal Processing Engineer...

• Your primary responsibility will be to design, develop, and assess sensor and source integration and data association and techniques for incorporation into tactical systems.
• You will learn about specific active and passive sensor types (RF, EO, IR, ES) and their associated data characteristics, track sources, sensor designs, modes of operation, sensor capabilities, detection and characterization data, and use your knowledge to integrate sensors, develop automated sensor data processing and conditioning algorithms to address false alarms and sensor artifacts (rings, splits, bias corrections), and associate sensor and characterization data for fusion with dissimilar data into a composite track.
• You will prototype concepts and algorithms for processing and integrating next generation sensor measurement and target characterization systems into advanced networked target identification and electronic protection capabilities.
• You will investigate and apply state of the art algorithms for track formation and prediction of challenging targets to include adaptive track formation from unassociated sensor measurements, track disclosure with false alarm control, measurement, track, and attribute association to tracks, maneuver detection and magnitude estimation, time synchronization, track-to-track correlation, and feature aided track ambiguity resolution.
• You will collaborate with a team of experts to perform analytics on complex sensor data to design novel techniques and criteria to rapidly disclose new tracks and adaptively control false track disclosure rates in challenging detection and high clutter environments.
• You will conduct tracking system design trade studies to identify, quantify, and demonstrate performance improvements achieved through the integration of the new candidate sensors or processing algorithms into existing tactical systems.

You meet our minimum qualifications for the job if you...

• Possess a MS degree in Electrical Engineering, Mathematics, Aerospace Engineering, or a related field.
• Have 5+ years of experience in designing and implementing sensor data processing, sensor data association, or target tracking algorithms and concepts.
• Have a theoretical background in statistical or adaptive signal processing.
• Have proficient analytical and applied mathematical skills.
• Have proficiency in MATLAB, Python, or similar programming languages for algorithm development or data analysis.
• Have the ability to perform effectively as part of a multi-disciplinary team.
• Are willing and able to travel up to 5% of the time to remote sites and are comfortable working in closed areas.
• Are able to obtain an Interim Secret security clearance by your start date and can ultimately obtain a Top Secret security 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.

You'll go above and beyond our minimum requirements if you...

• Possess a PhD degree in Electrical Engineering, Mathematics, Aerospace Engineering, or a related field.
• Have an active Secret security clearance.
• Have research, development, and analysis experience in some or all of the following:
• Probability and stochastic processes
• Target tracking algorithms and concepts
• Sensor fusion algorithms and techniques
• RF, Electronic Support, and/or EO/IR sensors and signals
• Control theory and Kalman filtering
• Detection and estimation theory

Why work at APL?

While the Johns Hopkins University Applied Physics Laboratory brings world-class expertise to a broad range of challenges, what makes us truly outstanding is our culture. We offer a vibrant, innovation ecosystem where you can feel safe to share ideas and to continue to grow personally and professionally. At APL, we celebrate our differences and encourage creativity and bold, new ideas and have earned Best Places to Work accolades in outlets such as Fast Companies and Glassdoor.

Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL’s campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at www.jhuapl.edu/careers.

#LI-KW1 

APL is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law.

APL is committed to promoting an innovative environment that embraces diversity, encourages creativity, and supports inclusion of new ideas. In doing so, we are committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accommodations@jhuapl.edu. Only by ensuring that everyone’s voice is heard are we empowered to be bold, do great things, and make the world a better place.

The referenced pay range is based on JHU APL’s good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.