Group 47 - Summer Research Program Intern (Sensor Development with Machine Learning)

The Energy Systems Group at MIT Lincoln Laboratory develops technology solutions that enhance the resilience and efficiency of both civilian and defense energy systems. This includes developing advanced architectures and system designs to improve the resilience of power grids, developing new control techniques for microgrids and distributed energy resources, and developing hardware and real-time simulation testbeds.

We seek a summer intern to work with a multi-disciplinary team that is developing mobile tracking applications to maximize the effectiveness of our situational awareness tools and to increase the resiliency of buildings and campuses in off-nominal states. 

Candidates will develop software modules that collect and process data from deployable sensor packages that have power, vibration, acoustic, RF, and electro-optical sensing modalities.  Candidates will develop real-time data processing, data processing techniques (machine learning and traditional), and human machine interface (HMI) operating pictures.

Potential projects include the following:

• Integrating electro-optical systems with data processing techniques to automate enumeration of vehicular traffic flows, generator status, and liquid storage tank fill levels.
• Vibration capture with data processing techniques to determine fundamental frequencies, equipment status, and general system states.
• Acoustic data capture to determine equipment status, analysis of fundamental frequencies, alarm detections, and alarm classifications.
• RF monitoring of wide and narrow band spectral power.

Candidates who are in the process of earning a B.S., M.S., or Ph.D. in electrical engineering, mechanical engineering, physics, mathematics, computer science, or other engineering discipline will be considered.

Desired Skills:

• Fluency with Python scripting
• Rudimentary knowledge of Machine Learning algorithms and techniques
• Rudimentary knowledge of data science and compression algorithms
• Strong problem-solving skills
• Detail oriented, able to multi-task, and have the ability to work autonomously for subsets of the summer
• Effective written and oral communications skills in technical environments