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PhD Student - Neuromotor Interfaces for Robot Teleoperation (sEMG + Egocentric Vision)

ETH Zurich · Zurich

New
Junior 🇬🇧 English
sEMG egocentric vision machine learning signal processing embedded systems Mixed Reality

Job description

About the role

The Sensing, Interaction & Perception Lab at ETH Zurich offers a fully funded PhD position in Zurich on neuromotor interfaces for dexterous robot teleoperation. The research combines surface electromyography (sEMG) measured at the wrist or forearm with egocentric vision, to decode hand and finger activity, continuous movement and motor intent in real time, while also capturing the context of the scene and the objects being manipulated.

Key responsibilities

  • Develop signal-processing and machine-learning methods for multichannel EMG, including discrete and continuous decoding of hand and finger activity
  • Develop egocentric computer-vision methods for understanding hands, objects, hand-object interactions, contacts, affordances and task state
  • Develop multimodal learning and reasoning methods that combine EMG with egocentric vision to infer motor intent and interaction context
  • Investigate reasoning over objects, actions, interaction sequences and task state to resolve ambiguous motor signals and anticipate intended actions
  • Apply methods to dexterous robot teleoperation, including mapping human motor intent to robot manipulators and dexterous hands
  • Optionally prototype wearable sensing systems (electrode configurations, signal acquisition, embedded processing, hardware and software integration)
  • Develop and evaluate applications in robotics, Mixed Reality and other interactive systems
  • Publish in top-tier venues and present at conferences, workshops and seminars

Required profile

  • Excellent written and spoken English
  • MSc, M.Eng. or equivalent in Computer Science, Electrical Engineering, Robotics or a related field
  • Strong foundation in machine learning (classification, regression, model evaluation, representation learning, generalization)
  • Solid understanding of signals and time-series data (sampling, frequency, phase, noise, spectral representations, filtering)
  • Strong programming skills and experience implementing and evaluating computational methods
  • Interest in real-time sensing and interactive systems, including physical sensors
  • Beneficial background in EMG or electrophysiological signals, robotics, computer vision, machine learning or interactive systems

What we offer

  • A fully funded PhD with an exciting research environment and team
  • Access to infrastructure for wearable and embedded prototyping, egocentric sensing, interactive systems and robotic manipulation
  • Collaboration with the ETH AI Center and ETHAR (the Augmented Reality hub with Google XR)
  • Support for publication and presentation at leading international venues

Applications are submitted online through the university's application portal: a one-page motivation letter, CV, transcripts and references. The earliest start is fall 2026.

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Published 5 hours ago

Expires 1 month from now

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ETH Zurich

Zurich