Radar Signal Processing Engineer-Associate Staff

Radar Signal Processing Engineer-Associate Staff Location: Lexington, MA, US Company: MIT Lincoln Laboratory 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. Responsibilities 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 Minimum Qualifications 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 from candidates of all backgrounds. If you are ready to join a team with a passion for pushing the boundaries of technology, we would love to hear from you! Recent Graduate Hiring Range: $116,400 - $140,000 Experienced Hiring Range: $116,400 - $182,200 Disclaimer: MIT Lincoln Laboratory provides a typical hiring range as a good faith estimate of what we reasonably expect to offer for this position at the time of posting. The final salary offered to a selected candidate will depend on various factors, including-but not limited to-the scope and responsibilities of the role, the candidate's experience, skills and education/training, internal equity considerations and applicable legal requirements. This range reflects base salary only and does not include additional forms of compensation or benefits. At MIT Lincoln Laboratory, our exceptional career opportunities include many outstanding benefits to help you stay healthy, feel supported, and enjoy a fulfilling work‑life balance. Benefits offered to employees include: Comprehensive health, dental, and vision plans MIT‑funded pension Matching 401K Paid leave (including vacation, sick, parental, military, etc.) Tuition reimbursement and continuing education programs A range of work‑life balance options ... and much more! Please visit our Benefits page for more information. As an employee of MIT, you can also take advantage of other voluntary benefits, discounts and perks. Selected candidate will be subject to a pre‑employment background investigation and must be able to obtain and maintain a Top Secret level security clearance with compartmented program eligibility MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required. #J-18808-Ljbffr