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Yayun Du

6 days ago

PhD Opening in Sensor-in-the-Loop Human-Robot Interaction at Vanderbilt University Vanderbilt University in United States

I am recruiting a PhD student in sensor-enabled human-robot interaction at Vanderbilt University.

Vanderbilt University

United States

email-of-the@publisher.com

Dec 28, 2025

Description

The SYMBIO-X Lab at Vanderbilt University, led by Assistant Professor Yayun Du, is recruiting one PhD student for Fall 2026 (with the option to start in Summer 2026). The research focuses on sensor-in-the-loop human-robot interaction, integrating multimodal physiological sensing with robotic control and reinforcement learning to enable safe and efficient human-in-the-loop autonomy. The lab is seeking candidates with strong quantitative skills and backgrounds in Electrical and Computer Engineering, Mechanical Engineering/Robotics, Computer Science, or Biomedical Engineering. Preferred qualifications include experience with ROS2, hands-on work with robotic arms (such as Franka, UR, xArm), and expertise in controls, reinforcement learning, or machine learning (PyTorch). Applicants should submit a CV, a short paragraph describing their interests, and optionally links to their GitHub or publications. The position is based at Vanderbilt University in the United States. Funding details are not specified, but PhD positions at Vanderbilt are typically fully funded. Interested candidates should contact Yayun Du directly via email and indicate their preferred start date.

Funding

No explicit funding details provided. Typically, PhD positions at Vanderbilt University are fully funded, but applicants should confirm funding and stipend details directly with the supervisor.

How to apply

Email yayun.du@vanderbilt.edu with your CV, a short paragraph describing your research interests, and optionally links to your GitHub or publications. Indicate your preferred start date (Fall or Summer 2026).

Requirements

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 expertise in controls, reinforcement learning, or machine learning (PyTorch). Candidates should be able to demonstrate relevant skills and experience through their CV and a short statement of interests.

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