The Surveillance Systems Group conducts research on integrated sensing and decision support architectures to support safe and efficient air and surface transportation. The group is currently leading efforts to develop a next generation airborne collision avoidance system for commercial aircraft and unmanned aircraft systems (UAS). Integrating UAS into the airspace is a national priority and a key research area for the group. Advances in autonomy and decision support will bring forth unprecedented changes to safety and efficiency for both air and surface transportation. To support these efforts our Group applies a broad base of analysis, modeling, optimization and machine learning/AI to develop sensing and decision support architectures to ensure safe and efficient autonomous systems.Job Description Job DescriptionA candidate with a strong background in machine learning, AI or computer science is needed to lead the design and application of surveillance and decision support architectures to support the safe and efficient integration of autonomous unmanned aircraft into the National Airspace and to develop and assess technologies for autonomous automobiles. Research will span areas related to safety and efficiency and include development and assessment of novel approaches for collision avoidance, optimal path planning, performance and safety analysis and associated modeling and simulation. Candidates must have strong familiarity with a variety of approaches to decision support solutions, including Markov Decision Processes, Machine Learning, optimization, and a demonstrated ability to select and implement the most appropriate methods. RequirementsPhD in Engineering or Computer Science with a focus on machine learning/AI. Experience with decision theory and artificial intelligence applied toward assessing the safety and efficiency of autonomous vehicle operation. Demonstrated ability to work with internal and external organizations in a team environment is required. Demonstrated ability to communicate and convey technical concepts in a clear, concise manner in written and oral forms is also required. 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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