Tracking and Data Fusion Engineer

APL is currently looking for a technical expert in state estimation and probabilistic reasoning to take on the role of Tracking and Data Fusion Engineer. The ideal team member is creative, fluent in mathematics, eager and quick to learn new skills and techniques, and a practical problem-solver able to bring structure to a complex problem, select the right tools to solve it, and create new tools when existing ones are inadequate.

We pride ourselves on pushing our highly-skilled team members to grow, specialize, and experiment in their own individual areas of interest, and to bring that unique expertise to bear on the critical challenges facing our nation. Become part of this innovative team at the forefront of groundbreaking technology development and analysis.

Duties for the Tracking and Data Fusion Engineer may include:

  • Analyze requirements for new and existing systems for defense against aircraft and ballistic and cruise missiles. Identify tracking and data fusion tasks that must be accomplished within the system to fulfill the requirements. Select established techniques appropriate to the particular system, its environment, and both technical and programmatic constraints.
  • Create prototype algorithms for tracking and data fusion. Efficiently apply existing tools to routine problems. Design solutions for novel and difficult problems by combining and extending existing techniques in novel ways. Integrate prototype algorithms with high-fidelity simulations. Analyze theoretical limits on algorithm performance and compare actual achieved performance to this standard using both simulated and real input.
  • Identify and understand instances where existing techniques and algorithms used in fielded products and entrenched in the thinking of current practitioners are limiting the performance of the overall system. Maintain awareness of advances in the state-of-the-art in both algorithms and in the networking and computing systems that feed and execute them. Realize when technological change has created new opportunities and propose innovative new approaches that offer added value to our sponsors and their missions. Conduct exploratory implementation and analysis to establish the feasibility and confirm the utility of new ideas.
  • Evaluate algorithm designs proposed to our sponsors by other organizations. Analyze expected and achieved performance, compare to theoretical limits and to results we have obtained with our own prototypes, and advise the sponsors on the suitability of the algorithms to the sponsor's mission and requirements.

The Johns Hopkins University Applied Physics Laboratory (APL) is a national leader in scientific research and development. In that spirit, the A3G group is looking to cultivate and encourage today's most innovative, ambitious, dedicated thinkers to propose new technologies and provide solutions for next-generation problems. With a vast network of cutting-edge technology and resources—and a laboratory full of brilliant minds—we invite you to apply for this competitive and rewarding position and to seize the opportunity to impact the world in which we live.

Note: This job summary and listing of duties is for the purpose of describing the position and its essential functions at time of hire and may change over time.

Required Qualifications:

  • Master's degree in Engineering, Mathematics, Computer Science, Physics or related field.
  • Three or more years of experience designing, implementing, and analyzing algorithms for state estimation, data fusion, and probabilistic reasoning.
  • Confident mastery of Bayesian inference and the Extended Kalman Filter.
  • Fluency in programming and analysis in MATLAB.

Desired Qualifications:

  • PhD in one of the above fields
  • Five or more years of experience, especially in tracking and data fusion for air and missile defense applications
  • 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 identification and classification techniques such as Support Vector Machines and Gaussian Mixture Models
  • Familiarity with radio frequency (RF) and infrared (IR) sensor systems, their physical phenomenology, and the practical issues these sensors raise for real-world tracking, classification, and data fusion systems that process their output
  • Fluency in a wide variety of programming languages, including MATLAB, C , Python, and Java, on both Linux and Windows platforms. Mastery of advanced language features such as object-oriented programming, templates, lambdas, and stream-style collection manipulation
  • Capability to design algorithms for parallelization. Competence with parallel computation techniques and tools, including POSIX and Windows multi-threaded programming, OpenMP, OpenCL, and CUDA
  • Excellent software engineering skills, including proficiency with both centralized and distributed version control systems, build systems and tool chains, issue trackers, and code review and documentation tools

Special Working Conditions: May require occasional travel.

Security: 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.

Benefits: APL offers a comprehensive benefits package including a liberal vacation plan, a matching retirement program, significant educational assistance, a scholarship tuition program for staff with dependents, and competitive salaries commensurate with skills and experience. For more information about our organization, please visit our web site at www.jhuapl.edu.

Equal Employment Opportunity: Johns Hopkins University/Applied Physics Laboratory (APL) is an Equal Opportunity/Affirmative Action employer that complies with Title IX of the Education Amendments Acts of 1972, as well as other applicable laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, sexual orientation, gender identity, national origin, disability, or protected Veteran status.


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