Jobs
Faculty Position in Autonomy, Navigation, & Mapping
The Department of Mechanical Engineering at Virginia Tech seeks applications for a tenure-track faculty position (assistant/associate/full) in the area of autonomy, navigation and mapping. Specifically, this open-rank position seeks applicants specializing in one or more areas of autonomy, perception, navigation, localization and mapping, and sensor fusion. The ideal candidate will contribute to ongoing research at Virginia Tech and will collaborate with existing faculty in robotics, automotive and aerospace fields in the development of autonomous vehicle/robotic systems. Candidates interested in enhancing navigation in complex environments for multi-agent systems, and ensuring uncrewed vehicle/robotic systems can operate safely and efficiently in diverse and unpredictable settings are encouraged to apply. This position will have valuable opportunities for interdisciplinary research and fostering innovation across departments. We aim to integrate strengths in robotics, computer vision, machine learning, and control systems to drive forward the state-of-the-art in autonomous technology. Additionally, the successful candidate will contribute to our educational mission by teaching core courses in robotics and controls, developing new specialized courses, and mentoring undergraduate/graduate students in advanced autonomous systems topics. We are seeking candidates motivated to contribute to a collegial, interdisciplinary community with a strong tradition of both fundamental and applied research.
Faculty Position in Robotics
The Department of Mechanical Engineering at Virginia Tech seeks applications for a tenure-track faculty position (assistant/associate) in intelligence, embodiment, and learning in robotics, effective August 2025. Given the rapid advancements and increasing integration of intelligence in robotics (including computational intelligence and physical intelligence), we seek candidates focused on fundamental research in robotics and robot learning, with a focus on areas such as vision and language models, continual learning, reinforcement learning, learning from demonstrations, representation learning, and morphological computation, with applications in diverse robotic tasks. We are interested in candidates who can catalyze the integration and analysis of data-driven and model-based techniques in robotics and control systems. Candidates interested in establishing tailored artificial intelligence (AI) and machine learning robotic courses for undergraduate and graduate students are encouraged to apply. We seek candidates motivated to contribute to a collegial, interdisciplinary community with a strong tradition of fundamental and applied research.