Doctoral Student in Neuromotor Interfaces for Dexterous Robot Teleoperation
Fully funded PhD position at ETH Zurich combining wearable EMG and egocentric vision for advanced robot teleoperation.
Best for:Best for machine learning and robotics researchers with a strong background in signal processing, wearable sensing, or computer vision.
Overview
The Sensing, Interaction & Perception Lab at ETH Zurich invites applications for a fully funded doctoral position focused on developing neuromotor interfaces for dexterous robot teleoperation. The research centers on combining surface electromyography (sEMG) with egocentric vision to decode human motor intent and understand environmental context in real time. The successful candidate will design robust computational methods, perform empirical evaluations, and collaborate with leading research hubs such as the ETH AI Center. Applicants are expected to hold an excellent master's degree in a relevant technical field and possess strong programming and machine learning skills.
What you'll do
- Develop signal-processing and machine-learning methods for multichannel electromyography (EMG) decoding.
- Design egocentric computer-vision algorithms for hand-object interaction and task state understanding.
- Implement multimodal learning frameworks combining neuromotor signals and visual data to infer user intent.
- Apply developed computational methods to real-time dexterous robot teleoperation and manipulation tasks.
- Disseminate research findings through publications in top-tier international venues and open-source contributions.
Requirements
Degree required: Master's degree (MSc, M.Eng., or equivalent) in Computer Science, Electrical Engineering, Robotics, or related field
Degree offered: PhD
Language: Written and spoken fluency in English
Instruction: English
Publications: Disseminate findings in publications at top-tier venues
- Strong foundation in machine learning including classification, regression, and representation learning
- Solid understanding of signals and time-series data analysis
- Strong programming skills and experience evaluating computational methods
- Demonstrated interest in building real-time sensing and interactive systems
- Hold an excellent master's degree or equivalent in a relevant field
Funding & terms
How to apply
Submit a complete application through the online portal, including a motivation letter of no more than one page, a CV, university transcripts, and contact details for academic references.
- Motivation letter
- Curriculum vitae
- Bachelor's transcript of records
- Master's transcript of records
- Contact details of 1–2 academic references
Contact
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