Yayun Du
11 months ago
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PhD Opening in Sensor-in-the-Loop Human-Robot Interaction at Vanderbilt University (Fall 2026) Vanderbilt University in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Expired
Country
United States
University
Vanderbilt University
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Keywords
About this position
The SYMBIO-X Lab at Vanderbilt University, led by Prof. Yayun Du, is recruiting one PhD student for Fall 2026 (with a possible Summer 2026 start) to work on sensor-in-the-loop human-robot interaction. The research focuses on integrating multimodal physiological sensing with robotic control and reinforcement learning to enable safe and efficient human-in-the-loop autonomy. The project will involve working with robotic arms (such as Franka, UR, or xArm), developing and implementing control algorithms, and leveraging machine learning techniques (especially using PyTorch) for real-world human-robot collaboration.
Applicants from Electrical and Computer Engineering, Mechanical Engineering/Robotics, Computer Science, or Biomedical Engineering backgrounds are encouraged to apply, especially those with strong quantitative skills. Preferred experience includes ROS2, hands-on work with robotic arms, and familiarity with controls, reinforcement learning, or machine learning. The lab values candidates who are motivated to work at the intersection of robotics, sensing, and intelligent systems.
To apply, interested candidates should email Prof. Yayun Du at [email protected] with a CV, a short paragraph describing their research interests, and optionally links to their GitHub or publications. The position is set to begin in Fall 2026, with the option to start in Summer 2026. For more information about the lab and research, visit the SYMBIO-X Lab website.
This opportunity is ideal for students interested in advancing the field of human-robot interaction, sensor integration, and autonomous systems within a leading research environment at Vanderbilt University.
Funding details
Available
What's required
Applicants should have strong quantitative skills and a background in Electrical and Computer Engineering, Mechanical Engineering/Robotics, Computer Science, or Biomedical Engineering. Preferred experience includes ROS2, hands-on work with robotic arms (such as Franka, UR, xArm), and knowledge of controls, reinforcement learning, or machine learning (especially with PyTorch). Candidates should be able to provide a CV, a short paragraph on research interests, and optionally links to GitHub or publications.
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Professors
Assistant Professor
United States
Research Interests
Artificial Intelligence
Human-robot Interaction
Computer Science
Biomedical Engineering
Electrical Engineering
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