PhD in Neuromotor Interfaces for Dexterous Robot Teleoperation

ETH Zurich; Zürich; On-site; CHF 42,000 - 54,000; Full time

Job summary

ETH Zürich’s Sensing, Interaction & Perception Lab invites applications for a fully funded PhD position at the intersection of robotics, wearable sensing, signal processing, machine learning, and human-computer interaction.

The project aims to develop neuromotor interfaces for dexterous robot teleoperation using surface EMG and egocentric vision, with multimodal learning to infer motor intent and context in real time. The position is open until filled and focuses on robust, generalizable systems.

Qualifications

• Strong foundation in machine learning, including representation learning and generalization.
• Experience with signals and time-series data (sampling, frequency, noise, filtering).
• Excellent programming skills and ability to quantitatively evaluate methods.
• Interest in building real-time sensing and interactive systems with physical sensors.

Responsibilities

• Develop signal-processing and machine-learning methods for multichannel EMG decoding.
• Develop egocentric computer-vision methods for hands, objects, and task state.
• Create multimodal learning and reasoning methods combining EMG with egocentric vision.
• Investigate reasoning over objects, actions, interaction sequences to anticipate motor intent.
• Apply methods to dexterous robot teleoperation and mapping human intent to robot manipulators.

Skills

Machine learning

Time-series signals

Programming

Real-time sensing

Education

MSc in Computer Science/EEE/Robotics

Job description

ETH Zürich’s Sensing, Interaction & Perception Lab invites applications for a fully funded PhD position at the intersection of robotics, wearable sensing, signal processing, machine learning, and human-computer interaction.

The project aims to develop neuromotor interfaces for dexterous robot teleoperation using surface EMG and egocentric vision, with multimodal learning to infer motor intent and context in real time. The position is open until filled and focuses on robust, generalizable systems.