Group 42--Summer Research Program Intern

Date: Mar 7, 2023

Location: Lexington, MA, US

Company: MIT Lincoln Laboratory

The Surveillance Systems Group conducts research, development and evaluation of novel surveillance systems and state of the art  integrated sensing and decision support architectures to support safe and efficient air and surface transportation. We are the world expert in airborne collision avoidance systems for crewed aircraft (https://www.ll.mit.edu/r-d/projects/airborne-collision-avoidance-system-x) and are currently leading efforts to develop sensing, vehicle to vehicle communications and machine learning based decision support to enable integration of increasingly autonomous systems, such as Uncrewed Aircraft Systems (UAS) and Advanced Air Mobility (AAM) platforms, into the US National Airspace System. We have received several R&D 100 awards for our surveillance and decision support technologies. Advances in surveillance, autonomy, and decision support will bring forth unprecedented changes to safety and efficiency for both air and surface transportation. To support these efforts, we apply a broad base of analysis, modeling, optimization and machine learning to develop sensing architectures and decision support tools to ensure safe and efficient operation of autonomous systems across the broader transportation domain.

Job Description

 

A summer intern is needed with an interest and background in applied engineering, surveillance systems, modeling and simulation, and/or algorithm development to support the development and implementation of safety critical systems to enable safe and efficient integration of increasingly autonomous systems into the transportation system. Example problem areas include analysis and algorithm development for surveillance systems and tracking algorithms, and evaluating system performance for vehicle separation and collision avoidance applications. Responsibilities will include algorithm development and assessment, modeling, simulation, and/or data analysis. The selected intern will be asked to carry out these tasks under the mentorship of a member of the Lincoln Laboratory technical staff. At the end of this time period, the student will be expected to present the results of their work.

 

Required qualifications:

 

  • Currently enrolled in an accredited college program
  • Working towards a graduate or undergraduate degree in Engineering (any type), Computer Science, Physics or Mathematics or a similar field
  • Proficient at high-level prototyping software languages (e.g., MatLab, Python, Julia)
  • Demonstrated ability to collaborate well as part of a team with good interpersonal skills
  • Demonstrated ability to communicate clearly to a wide spectrum of audiences

 

Desired qualifications:

 

  • Experience or interest in developing algorithms and mathematical models in a simulation environment
  • Knowledge in the fields of probability theory and software development
  • Experience with the development and evaluation of machine learning/AI applications
  • Experience in other programming languages, such as C and C++
  • Experience processing and analyzing large sets of real-world data
  • Exposure to the air, surface, or maritime transportation domain
  • Experience with standard machine learning/deep learning libraries such as Tensorflow, PyTorch, Scikit-Learn

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.

 

To safeguard our health and well-being, MIT Lincoln Laboratory requires COVID-19 vaccination for all employees.  Individuals may request exemption from the vaccine requirement for medical or religious reason.

 

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.

 

Requisition ID: 38841 


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