2026 PhD Graduate - Radar, Machine Learning, Signal Processing, Data Science

Overview 2026 PhD Graduate - Radar, Machine Learning, Signal Processing, Data Science at Johns Hopkins Applied Physics Laboratory (APL). 2 weeks ago — Be among the first 25 applicants. Base pay range $102,500.00/yr - $227,500.00/yr Description Are you interested in applied R&D? Do you enjoy working in a creative environment, as part of a varied team of engineers, physicists, and computer scientists? Do you want to play a critical role in the defense of our country — at sea and at home — from advanced missile threats? We are seeking highly motivated PhD graduates in Electrical Engineering (EE), Electrical and Computer Engineering (ECE), Computer Science (CS), Physics, or a similar technical degree. We are particularly interested in self-guided, creative problem-solvers who can develop into future technical leaders for our research performed for the US Navy and other DoD sponsors. Responsibilities Participate in live radar testing and analyze recorded data to gain insights into system performance, particularly with regard to environmental effects/physics. Develop and apply detailed, physics-based simulations written in Java, C/C++, Matlab, and Python. Learn and creatively apply machine learning, signal processing, and data science to real-world problems that no one else has previously solved. Develop novel instrumentation and algorithms for understanding RF propagation effects by directly measuring, recording, and analyzing RF signal measurements. Learn, apply skills, and advance the state of the art in core technology areas of signal processing, electromagnetics, software development, and boundary-layer meteorology. Develop skills to lead technical teams toward common goals. Directly communicate results to sponsors and contractors to guide the directions of DoD programs toward technical success. Qualifications Have a PhD degree in EE, ECE, CS, Physics, or a similar technical field, with a GPA above 3.5. Are familiar with Python, Matlab, or equivalent, or have had some exposure to modern development processes (git, GitLab, Jira, or equivalent). Have a strong understanding of, and interest in, machine learning, data science, signal processing, and/or electromagnetic theory. Are able to obtain an Interim Secret level security clearance by start date and can ultimately obtain a Secret level 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. Preferred qualifications Cross-discipline technical degrees, including minors in EE, ECE, CS, Physics in addition to a PhD. Radar or RF research experience (hardware, antennas, remote sensing, tracking, etc.). Internship experience related to DoD research, DoD contractors, or the advanced-technology industry. About Us The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to defense, security, space and science challenges. 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. APL celebrates diverse perspectives and creativity. Our employees enjoy generous benefits, including education assistance, retirement contributions, and work/life balance. Learn more at 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, disability, veteran status, or any other characteristic protected by law. APL provides reasonable accommodations to individuals of all abilities. For accommodation requests, contact View email address on click.appcast.io. The referenced pay range is based on good faith belief at the time of posting. Actual compensation may vary based on location, experience, and other factors. For salaried employees, hours may be prorated if Applications are accepted on a rolling basis. Location: Bethesda, MD #J-18808-Ljbffr Johns Hopkins Applied Physics Laboratory