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Changliu Liu

Top university

6 months ago

Postdoctoral Fellow in Formal Verification and Safe Control for Humanoid Robotics Carnegie Mellon University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Postdoctoral fellow position; funding details are not specified in the post.

Deadline

Expired

Country flag

Country

United States

University

Carnegie Mellon University

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Keywords

Computer Science
Machine Learning
Mechanical Engineering
Electrical Engineering
Mathematics
Robotics

About this position

Carnegie Mellon University’s Robotics Institute is hiring Postdoctoral Fellow(s) in the Intelligent Control Lab with a research focus on formal verification and safety of perception-based humanoid robot control systems. The work emphasizes human-humanoid interaction and aims to develop principled methods for reliable and safe operation of humanoid robots in human-centered environments.

This opportunity sits at the intersection of Robotics, Computer Science, Mathematics, and Electrical/Mechanical Engineering, with strong relevance to neural network verification, safe learning and control, machine learning, and foundation models. The position is ideal for candidates interested in trustworthy robot autonomy and rigorous methods for safety-critical robotic systems.

Eligibility: applicants should hold a PhD in a relevant field such as Robotics, ECE, CS, ME, or a related area. The post specifically highlights experience or interest in formal methods, safe control, and machine learning for robotics.

Location: Pittsburgh, Pennsylvania, United States.

Application: apply via the provided link and send a CV, research statement, and up to three references to the announcer. No deadline was stated in the post.

Funding details

Postdoctoral fellow position; funding details are not specified in the post.

What's required

PhD in a relevant field such as Robotics, ECE, Computer Science, Mechanical Engineering, or a related discipline. Preferred backgrounds include formal methods such as neural network verification, safe learning and control for robotics, and machine learning or foundation models. Applicants should be prepared to work on formal verification and safety of perception-based humanoid robot control systems and human-humanoid interaction.

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Professors

Associate Professor

University Name
Country flag

United States

Research Interests

Human-robot Interaction

Computational Neuroscience

Task Planning

Multi-robot Systems

Model Checking