Job Information
MIT Lincoln Laboratory AI & Signal Processing Engineer (Assistant Staff) in Lexington, Massachusetts
The Tactical Edge Communications Group develops and demonstrates new algorithms, architectures, and hardware implementations for processing signals for a broad range of RF system applications, including advanced wireless communications and signals intelligence. The group's core competencies include developing algorithms and system concepts for communication, signal detection, localization, and classification in challenging environments, as well as hardware implementations and prototypes of these advanced RF systems. The group has expertise in adaptive antenna array processing, signal detection and estimation, statistical inference, pattern recognition, multichannel communications, wideband sampling techniques, antenna and RF subsystem design, and systems analysis. The group is applying machine learning techniques to spectrum operations problems. The group is also interested in exploring methods for (distributed) control and monitoring of networked control systems, with applications specific to RF communication systems. The staff members have advanced degrees in electrical engineering, physics, and applied mathematics. To support concept development and evaluation, the group conducts a significant amount of field tests and data collection campaigns, and collaborates with other groups within the division and throughout the Laboratory in real-time prototype implementation, experiment execution, and systems analysis.
The Position:
The Group is seeking creative and enthusiastic candidates with an interest in applying signal processing and artificial intelligence techniques to develop novel algorithms that enable new capabilities in next-generation RF communication systems. Typical assignments include algorithm design, analysis, and implementation; communication system analysis; software and hardware prototyping and test activities; documentation and planning; and field experimentation, data collection, and post-experiment analysis. Staff in this Position will receive mentorship from senior engineers in order to grow into roles with increasing responsibility and broadening impact.
Required Skills:
B.S. Degree in Engineering, Computer Science, Physics, Mathematics or related field
Experience with scripting and analysis tools such as Matlab and Python
Highly effective written and verbal communication skills
Ability to work effectively in a team and set priorities
Outstanding analytical and problem-solving skills
Preferred Skills:
Coursework or experience in wireless communication systems, information theory, detection and estimation theory, stochastic processes, and/or linear algebra
Experience applying unsupervised and supervised machine learning techniques to solve signal/data processing problems
This position will include a mixture of on-site, travel, and remote work as needed to support integration and field events.
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
Mentorship programs
A range of work-life balance options
... and much more!
Please visit our Benefits page (https://hr.mit.edu/benefits) for more information. As an employee of MIT, you can also take advantage of other voluntary benefits, discounts and perks (https://hr.mit.edu/benefits/additional) .
Selected candidate will be subject to 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 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.
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