36: Tech Staff - Autonomy

The Integrated Missile Defense Technology group is seeking an autonomous systems research scientist to join a nationally impactful team and to develop novel algorithms for the coordination and control of next generation autonomous vehicles. Some examples of research and development areas of interest to the group include robust multi-agent decision making and coordination for large groups of heterogeneous platforms, machine learning accelerated optimization techniques, vision-based navigation algorithms including applying machine learning approaches to navigation in challenging environments without GPS, and the control of flight vehicles with challenging dynamics under safety constraints.

We are actively seeking highly motivated and exceptionally bright individuals who can think broadly, analyze complex problems deeply, implement solutions in a rapid prototyping environment, and wish to contribute to the development of cutting-edge technology to enhance National Security. This position provides an opportunity to perform state-of-the-art, mission-driven research and development in collaboration with experts at both MIT Lincoln Laboratory and top universities.

The role is focused on algorithm development for autonomous systems, particularly techniques supported by optimization, control theory, and formal methods. Typical tasks in this role involve developing algorithms and simulations, implementing embedded code, reading and writing research papers, meeting with collaborators and government sponsors, and prototyping and testing integrated systems. The successful applicant will have experience with modern autonomy algorithms and must have a strong foundation in software engineering and computer science principles.

• PhD in Electrical Engineering, Systems Engineering, Mechanical Engineering, Aero/Astro, Computer Science, Robotics or related field
• In lieu of a PhD, an MS with 3+ years of directly related experience will be considered
• The ability to apply existing talents to new fields at both the technically detailed and big picture levels
• Candidates must have demonstrated team leadership qualities and effective communication
• Strong programming skills in at least one commonly used programming language (e.g. C/C++)
• Strong mathematical skills demonstrated through classwork and/or peer-reviewed publications

• Flight vehicle dynamics and controls (e.g., modern feedback control and state estimation)
• Planning, decision making, and computer vision algorithms (e.g., convolutional neural networks, reinforcement learning, and formal methods approaches)
• Optimization theory (convex, non-convex, mixed-integer, etc...)
• Nonlinear optimal control
• Machine learning for perception and control
• Motion planning
• Planning under temporal logic constraints
• Formal methods including synthesis, verification, and model checking
• Control barrier functions and other certificate methods
• Contract-based design
• Differentiable programming
• Strong programming skills in ROS, Python, and C/C++ and experience with real time operating systems