Radar Signal Processing Engineer-Associate

Position Description

MIT Lincoln Laboratory is seeking a talented signal processing researcher to join our dynamic team. As a member of the Airborne Radar Systems and Techniques group at MIT Lincoln Laboratory, you will work on world‑class sensor systems as part of a team with a variety of technical backgrounds. We model and analyze the performance of new technologies, prototype radio frequency and complimentary sensors, design and execute data collections, and develop algorithms to detect, track, and image challenging targets within complex environments.

Our models and algorithms benefit from access to a one‑of‑a‑kind interactive supercomputer. Our prototypes and data collections are enabled by highly adaptable test infrastructure including two airborne radar testbeds—including a turboprop aircraft equipped with an advanced radar, visible and infrared imaging system, communications systems, and real‑time data processors—and modern jammers.

Early career candidates and recent graduates are strongly encouraged to apply, and if selected, will work alongside experienced group members to learn about our mission areas and identify career growth paths. We are particularly interested in candidates with a relentless curiosity and strong technical foundation in Electrical or Computer Engineering, Mathematics, Physics, or a related field with experience in signal/imaging processing, data analysis, or radio frequency systems.

• Collaborate with experienced staff on the design, simulation, implementation, and optimization of signal and image processing algorithms
• Analyze and interpret data sets to extract meaningful insights, assess system behavior, and evaluate the performance of new algorithms
• Contribute to the design and execution of experiments that include both ground‑based and airborne sensors
• Prepare technical documentation, including test plans, interface control documents, reports, and technical presentations

• Master’s degree in Electrical Engineering, Computer Engineering, Mathematics, Physics, or a related field. In lieu of a Master’s, a Bachelor’s degree with 3 years of relevant work experience will be considered
• Experience in programming languages such as MATLAB, Python, or C/C++ along with standard data/signal/image processing and machine learning libraries
• Strong organizational and problem‑solving skills with the ability to work independently as well as collaboratively with a team
• Effective communication skills, including ability to convey research goals, processes, accomplishments, and technical concepts
• Ability to participate in field tests, data collection campaigns, and system demonstrations with occasional travel

Our team has a wide variety of professional experiences and educational backgrounds that enable us to find creative solutions to challenging real‑world problems. We value university research experience, Master’s thesis work, journal or conference submissions, and capstone or senior design projects. Applicants are not expected to have experience in all the following areas, however, a deep understanding of some and the desire and ability to learn others is expected.

• Technical courses including classical mechanics, electromagnetism, waves and optics, mathematical methods for scientists, linear algebra, differential equations, probability and statistics, digital signal processing, artificial intelligence and machine learning, remote sensing, and robotics
• Prototype, testing, and laboratory experience including experience with amplifiers, antennas, analog and digital filters, radio frequency systems on chip (RFSoC), field programable gate arrays (FPGAs), central/graphics processing units (CPU/GPUs), oscilloscopes, and spectrum analyzers
• Signal/imaging processing and data analysis techniques including eigen‑decomposition, Z and Fourier transform, finite/infinite impulse response filters (FIR/IIRs), transformers and other neural networks, and adaptive estimation

Join us in an intellectually rewarding, collaborative environment where you will further develop and apply your technical skills to real‑world challenges. We value differences and encourage applications…