Autonomous Systems Research Engineer: Info-Driven Control

University of Texas; Utah; On-site; USD 120,000 - 150,000; Full time

Job summary

The University of Texas at Austin's Oden Institute seeks a Research Engineer to develop information-aware trajectory planning and control for autonomous aircraft as part of the DARPA CyPhER Forge program.

You will lead design and deployment of algorithms and contribute to robotics, optimization, and learning-based control while collaborating with multidisciplinary teams across simulations and hardware.

Qualifications

• Ph.D. or equivalent industry experience in a relevant field.
• Strong background in control, trajectory optimization, and machine learning.
• Experience with aircraft dynamics, flight control systems, and autonomous vehicle control.
• Experience developing large software projects (>10,000 lines of code) in Python/C++ or similar.
• Excellent communication and collaboration skills.

Responsibilities

• Develop and implement trajectory planning algorithms for autonomous aircraft.
• Design robust control strategies bridging models and multiphysics dynamics.
• Integrate planning with control to enable learning and uncertainty reduction.
• Develop and maintain large-scale software for autonomous systems research.
• Collaborate with multidisciplinary teams to validate algorithms via simulation and hardware.
• Publish findings and contribute to DARPA CyPhER Forge milestones.

Skills

Control theory

Trajectory optimization

Machine learning

Aircraft dynamics

Flight control

Autonomous vehicles

Large software projects

Python

C++

Communication skills

Education

Ph.D. in Aerospace Engineering, Control Systems, Robotics, Computer Science, or related field (or equivalent industry experience)

Tools

ROS

Job description

The University of Texas at Austin's Oden Institute seeks a Research Engineer to develop information-aware trajectory planning and control for autonomous aircraft as part of the DARPA CyPhER Forge program.

You will lead design and deployment of algorithms and contribute to robotics, optimization, and learning-based control while collaborating with multidisciplinary teams across simulations and hardware.