MIT Lincoln Laboratory, located in Lexington, Massachusetts, is a United States Department of Defense research and development center chartered to apply advanced technology to problems of national security. The Laboratory provides technical expertise to the US government in domains ranging from cybersecurity to novel radar design to advanced microelectronics, and more. http://www.ll.mit.edu.

　　The Advanced Lasercom Systems and Operations Group develops, builds, tests, and operates laser communications systems for a variety of applications and environments. Lasercom offers dramatically increased data rates and enhanced physical security relative to standard radio frequency-based communications systems. The Group has expertise in communications; optics; electro-optics; optical turbulence mitigation; precise pointing control systems; embedded systems; command, control, and telemetry; test set design and fabrication; data analysis; modeling; and simulation.

　　Job Description:

　　Typical machine learning applications involve the development of classification or time-series prediction models trained on large static data sets. In certain real-world applications, either (a) the available real-world data sets are too sparse, or (b) the environment is non-stationary, so that the model trained only on an initial data set loses its relevance. There are several potential applications within the Group, relating to pointing, acquisition, and tracking of optical beams propagating through media varying at multiple time scales. Only sparse data sets are available with real-world measured data.

　　The Summer Intern will develop adaptive machine learning frameworks to enhance accuracy of optical beam pointing and tracking when propagating through a dynamic medium with subsonic or supersonic turbulence. Framework development and initial validation will be through nominally generated synthetic data sets, while being adaptable to future instrumented systems. Familiarity with machine learning and its applicability to computational fluid dynamic modeling and prediction are highly desirable skill sets. The specific project(s) will be tailored to the intern’s individual technical experience and interests.

　　Requirements:

　　The candidate should be working towards a Bachelor’s, Master’s or Doctorate degree in Electrical Engineering, Computer Science, Statistics, Data Science, Machine Learning, Aero-/Astronautical Engineering, Applied Physics/Astronomy, Bioinformatics, or a related field, with a minimum cumulative GPA of 3.5.

　　The intern should have experience relevant to developing machine/deep/reinforcement learning models and associated pipelines. The intern should have experience with Pytorch, Python or MATLAB® and be proficient working with Jupyter notebooks.

　　Experience in the following areas is desired, but not required:

　　Familiarity with camera performance metrics, and data capture / logging using high-speed digital cameras

　　Familiarity with time series modeling and prediction

　　Familiarity with fluid dynamics, including shock waves and boundary layers

　　Basic knowledge of laser physics and optical beam propagation

　　Demonstrated communication skills (both oral and written)

　　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.

　　Requisition ID: [[id]]