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Associate Staff Engineer in Radar Signal Processing
2 months ago
MIT Lincoln Laboratory is on the lookout for a skilled individual to become a part of our innovative team as an Associate Staff Engineer specializing in Radar Signal Processing.
As a key member of the Airborne Radar Systems and Techniques group, you will engage in the development of high-performance sensor systems alongside a team of professionals with varied technical expertise.
Your role will involve prototyping radar and imaging sensors aimed at wide-area surveillance, experimenting with cutting-edge radar technologies, and refining algorithms for detecting and imaging objects in challenging environments.
Projects will typically encompass a blend of system analysis, hardware and software development, and algorithm design.
Our multidisciplinary teams collaborate to grasp foundational physics, design and construct unique sensor systems, orchestrate and execute flight test data collections, innovate and integrate novel processing techniques, and investigate advanced countermeasures that may impact sensor performance.
We strongly encourage early career candidates to apply. If selected, you will have the opportunity to work alongside seasoned group members to gain insights into our mission areas and identify potential career advancement paths.
We are particularly interested in candidates with a background in Electrical Engineering, Computer Engineering, Mathematics, Computer Science, or a related discipline, who possess a genuine interest and foundational knowledge in signal processing techniques.
While experience with radar systems, remote sensing, or signal/image processing applications is advantageous, it is not a prerequisite.
Key Responsibilities• Analyze and interpret radar data sets to derive significant insights and improve system performance.
• Contribute to the development of signal processing algorithms utilizing MATLAB and Python.
• Collaborate with experienced mentors to implement and assess physics-based and AI/ML techniques for automatic target recognition, signal denoising, target tracking, and interference mitigation.
• Work together on the design and execution of experiments for both ground-based and airborne sensors.
• Prepare technical documentation including status reports, test plans, and interface control documents, and deliver technical presentations.
Desired Qualifications
• Master’s Degree in a relevant field or a Bachelor’s Degree with 5+ years of pertinent work experience.
• Familiarity with digital and statistical signal processing, machine learning, and/or image processing techniques.
• Proficiency in MATLAB or Python (or both). Familiarity with other programming languages, such as C/C++, is a plus but not mandatory.
• Understanding of RF hardware (amplifiers, antennas, filters), digital processing, and/or control systems (FPGAs, GPUs, CPUs) is desirable but not required.
• Strong organizational, problem-solving, and communication skills.
• Ability to work effectively both independently and as part of a team.
Join us in a stimulating academic environment where you will have the chance to apply your expertise to real-world challenges in radar signal processing. We value diversity and encourage applications from candidates of all backgrounds.
Benefits
At MIT Lincoln Laboratory, we offer exceptional career opportunities along with numerous benefits designed to support your health, well-being, and work-life balance. Benefits 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.
• Mentorship programs.
• A variety of work-life balance options.
... and much more.
Selected candidates will undergo a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance. MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment without discrimination based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required.
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