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Data Fusion and Tracking Section Supervisor
Johns Hopkins Applied Physics Lab in Laurel, Maryland
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Date Posted September 11, 2019
Employment Type Full-time
Application Deadline Open until filled

Job Description 

Data Fusion and Tracking Section Supervisor - A3G-5-21911 


Position Description

Are you passionate about solving technical challenges related to data fusion and tracking? 


Do you find developing and inspiring others to reach their maximum potential rewarding?


If so, we're looking for someone like you to join our team at APL.


We are seeking a technical authority and strong leader to be a part of our team. The A3G-5 Section Supervisor will lead A3G-5 and assist the A3G Group Supervisor in leading our group of savvy scientists and engineers focused on developing advanced technologies and algorithms in support of the Air and Missile Defense mission. We are looking for a tried-and-true leader and domain expert who can offer technical contributions to projects that employ advanced technology development, data fusion, and tracking techniques to solve critical AMDS problems.


As a Data Fusion and Tracking Section Supervisor...


·       You will contribute significantly to the evolution and implementation of the A3G group vision, strategy, and execution (VSE) plan where the activities of your section staff provide part of a foundation for that VSE. Propose research initiatives and implement inspiring strategies to address current and future challenges facing air and missile defense. Set a clear vision and path for the section and prioritizing analysis needs

·       You will recognize analysis needs, work with supervisors/task leaders to evaluate the needs of their respective process, and figure out the type of analysis tasks required. Craft a team of domain experts and employ the best tool sand methods to answer the sponsors’ questions. Interface heavily with sponsors and management both within and outside of APL. Analyze data fusion and tracking results to draw robust inferences about pertinent phenomena and their consequences on combat system behavior and performance. Compile technically solid conclusions and communicate clear recommendations to the sponsor.

·       You will actively engage and partner with section staff to assess their strengths and their limitations. Work with staff to understand their career objectives and seek to match staff development with project objectives. Mentor and coach staff members. Provide and guide staff development opportunities, including the annual performance coaching process.

·       You will assess the section’s current and future work and define and propose the analytical and physical infrastructure necessary to carry out that work. This may include suggesting new improvements to facilities, computing resources, tools, laboratories, work spaces, etc. Assist with the annual capital and task planning processes.


·       You will provide supervision and staff planning, including monitoring technical work for accuracy and quality. Delegate and assign task assignments to analysis team members and handle efficient execution for individual responsibilities. Assist the group supervisor in the interviewing and hiring processes. Assist with, and implement, staff development initiatives, including staff mentoring, onboarding, and working with staff to understand their career objectives.



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


·       Possess a Master’s degree in Engineering, Mathematics, Computer Science, Physics, or related field

·       Have 5+ years of experience crafting, implementing, and analyzing algorithms for state estimation, data fusion, and probabilistic reasoning

·       Are familiar with both homogeneous and heterogeneous data fusion

·       Have confidently mastered Bayesian inference and the Extended Kalman Filter

·       Are fluent in programming and analysis in MATLAB and/or Python

·       Have staff development and/or mentoring experience

·       Have a track record of strong leadership skills

·       Have the ability to obtain a Secret security clearance. Applicant selected 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...


·       Have a PhD in Engineering, Mathematics, Computer Science, Physics, or related field

·       Have 4+ years of experience in designing and implementing data fusion and/or tracking algorithms for a variety of datasets

·       Possess theoretical knowledge of and practical experience with advanced estimation techniques such as Multiple Hypothesis Tracking, Particle Filtering, Unscented or Sigma-Point Kalman Filtering, Gaussian Mixture Filtering, and Probability Hypothesis Density Filtering

·       Have knowledge and experience with data fusion related to both active and passive sensors

·       Have experience using high performance computing structures like GPU’s and CPU clusters

·       Are familiar with radio frequency (RF) and infrared (IR) sensor systems, their physical phenomenology, and the practical uses of these sensors in real-world applications for tracking, classification, and data fusion 

·       Are competent in a wide variety of programming languages, including C++ and/or Java on both Linux and Windows platforms

·       Have the ability to obtain a Top Secret security clearance


Why work at APL?


The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation’s most critical defense, security, space and science challenges. With a wide selection of challenging, impactful work and a robust education assistance program, APL promotes a culture of life-long learning. Our employees enjoy generous benefits and 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.



APL is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability status, veteran status, or any other characteristic protected by applicable law.

Primary Location

 *United States-*Maryland-*Laurel
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