Data Fusion and Tracking Section Supervisor - A3G-5
Laurel, MD

Job Description

Data Fusion and Tracking (A3G-5) Supervisor

The Advanced Concepts and Technologies Group (A3G) in the Combat Systems Branch of the Air and Missile Defense Sector (AMDS) is currently looking for a technical authority and strong leader to take on the position of Section Supervisor of the Data Fusion and Tracking section (A3G-5). The A3G-5 Section Supervisor will lead A3G-5 and assist the A3G Group Supervisor in leading a group of savvy scientists and engineers focused on developing advanced technologies and algorithms in support of the Air and Missile Defense mission. The individual chosen for this position is 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.

We pride ourselves on pushing our highly-skilled team members to grow their specific areas of expertise to better solve the critical challenges facing our nation. Become part of this creative team at the forefront of groundbreaking technology development and analysis.

Duties for the A3G-5 Section Supervisor include:

Mission Effectiveness: 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 implementing 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.

Organizational Competencies: Recognize analysis needs, work with supervisors/task leaders to evaluate the needs of their respective process, and figure out 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.

Staff Development: Actively engage and partner with section staff to assess their strengths and their limitations. Work with staff to understand their career objectives and seeking to match staff development with project objectives. Mentor and coach staff members. Provide and guide staff development opportunities, including the annual performance coaching process.

Resources: 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.

Functional Responsibilities: 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. Support the section and its staff members by implementing AMDS and Laboratory policies and procedures.

You meet our minimum requirements if...

* You have a master's degree in Engineering, Mathematics, Computer Science, Physics, or related field
* You have 5 years of experience crafting, implementing, and analyzing algorithms for state estimation, data fusion, and probabilistic reasoning
* You are familiar with both homogeneous and heterogeneous data fusion
* You have confidently mastered Bayesian inference and the Extended Kalman Filter
* You have fluency in programming and analysis in MATLAB and/or Python
* You have staff development and/or mentoring experience
* You have a track record of strong leadership skills
* You hold a Secret security clearance

You go above and beyond our expectations if you have...

* A PhD in Engineering, Mathematics, Computer Science, Physics, or related field
* 4 years of experience in designing and implementing data fusion and/or tracking algorithms for a variety of datasets
* 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
* Knowledge and experience with data fusion related to both active and passive sensors
* Experience using high performance computing structures like GPU's and CPU clusters
* Familiarity 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
* Competence in a wide variety of programming languages, including C and/or Java on both Linux and Windows platforms
* 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.