Are you self-motivated and passionate about pushing the boundaries of advanced data analytics for all forms of theater defense in a creative and collaborative laboratory environment?

Do you enjoy coming up with innovative solutions to complex and unusual technical problems?

If so, we're looking for someone like you to join our team!

The C2 Resilience Sciences Group at The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is seeking an Applied Research Scientist with a desire to conduct algorithm development, modeling and analysis using statistical signal processing, multi-domain data fusion, and deep learning concepts to help enable innovative, effective, and affordable system solutions to the most difficult challenges posed by evolving air, missile, and surface threats.

• You will contribute to the development of resilient theater defense systems using advanced sensor sources and dynamic fusion algorithms that can simultaneously execute sensing, communication, and electronic warfare functions
• You will document technical results and communicate your findings and recommendations to APL staff, contractors and sponsors. You will write reports and algorithm descriptions and present analysis results, and status updates
• You will remain at the forefront of the latest technological developments in the industry
• You will initiate and engage independent research and development projects that encourage creative solutions and reward independent initiative

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

• Possess a Ph.D. in Electrical Engineering, Applied Mathematics, or a related field
• Have background in one or more of the following broad research areas:
• Statistical signal processing (detection theory, estimation theory, and tracking)
• Radar signal processing
• Image processing (with Electro-Optical and Infrared (EO-IR) sensor data)
• Pattern Recognition and Classification (parametric, non-parametric and data driven methods)
• Deep Learning (Convolutional Neural Networks, Generative Adversarial Networks, Recurrent Neural Networks, Reinforcement Learning, etc..), Explainable AI
• Multi-sensor and Multi-modal data fusion (EO-IR and RF data fusion, upstream data fusion, decision-level fusion), Low dimensional signal processing
• Have experience using MATLAB, Python, and/or C/C++ for algorithm development, modeling and simulation
• Have the ability to perform effectively as part of a multi-disciplinary team
• Can clearly communicate ideas and results
• Are able to obtain a Secret level 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

• Have peer-reviewed publication history and briefed external audiences
• Have experience working on technical efforts in the air and missile defense community
• Have practical experience applying deep learning and advanced signal processing techniques with radio frequency (RF) and/or EO-IR sensors and signals
• Have working knowledge of Deep Learning Platforms (TensorFlow, PyTorch).
• Hold an active secret clearance.

Why work at APL?

JHU/APL brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.

At APL, we celebrate our diversity and encourage creativity and bold, new ideas. 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.

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.