PhD position: Input Detection for Augmented Reality via Learning-based EMG/EOG/EEG Event Detection 100%, Zurich, fixed-term The Sensing, Interaction & Perception Lab invites applications for a PhD position in Computational Interaction, focusing on sensor-based input detection for Augmented and Mixed Reality. This research combines physiological time series analysis (EEG, EMG, EOG), machine learning, and real-time system design for intelligent interaction systems. The research will contribute to the area of neural input systems and will be related to brain-computer interaction. Candidates ideally have a background in Computer Science, Electrical Engineering, or Robotics and prior experience with event detection in differential recordings. Additional familiarity with building your own embedded sensing setup is a strong plus. An optimal background for the project would be Electrical Engineering bachelor's (sensing, signal processing) with a more Computer Science-oriented master's (machine learning, time series processing). Project background Emerging AR/VR interfaces are limited by the input modalities they rely on and existing input devices have a limited bandwidth: pointing, clicking, typing. The future of Augmented and Mixed Reality systems promises much broader bandwidth for sensing input from a user through brain-computer interaction. In this project, we aim to explore sensor-based approaches—starting with EEG and later incorporating EMG/EOG—to detect input and user intent. We will explore how sensed differential signals can be leveraged for input, interaction, and adaptive control in MR environments. Central challenges include signal denoising, signal processing, robust event detection, and modeling shifts across sessions and users. Job description Develop machine learning pipelines for EEG/EMG/EOG time series processing with a focus on event detection and real-time interaction. Investigate distribution shifts in physiological data and apply continual learning or transfer learning approaches. Design and run controlled experiments for data collection in lab and AR environments. Ideally also devise your own EMG/EOG embedded sensing setup and evaluate edge-AI techniques Collaborate on building interactive prototypes and validating input systems in AR/VR with others in our interdisciplinary research team. Disseminate your findings in publications at top-tier venues and open-source your results tools. Present research findings at academic conferences, workshops, and seminars. Profile ETH requirements: written and spoken fluency in English an excellent master's degree (MSc., M.Eng. or equivalent) in Computer Science, Electrical Engineering, Robotics, or related field requirements for the position: Solid knowledge of machine learning, particularly for time series analysis and event detection Solid programming skills in C#, C++, or .NET-based languages (in addition to Python) Experience with differential signals (EEG, EMG, EOG, or similar) Familiarity with experimental design and empirical validation methods optional but useful: prior experience with AR/VR and Unity/Unreal beneficial Background in online learning or adaptive systems Familiarity with Unity, AR/VR development, or real-time interfaces Building your own embedded sensing setup is a strong plus Experience conducting user studies Knowledge of biosignal acquisition hardware or even having built your own EEG/EMG/EOG sensing setup Past experience with brain-computer interaction Workplace We offer We offer an exciting environment and team to study in and work with. Beyond the lab, ETH Zürich has several internationally recognized research groups dedicated to interactive systems, Human-Computer Interaction, AR/VR, health, and machine learning. In our research, we often collaborate with other groups and departments as well as with several other institutions and companies in Switzerland and abroad. During your PhD, you will have the opportunity to contribute to and collaborate with the ETH AI Center and engage in ETHAR, ETH's Research Hub for Augmented Reality in collaboration with Google XR. chevron_right Working, teaching and research at ETH Zurich We value diversity In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Curious? So are we. Please submit your complete application through the online application portal: Motivation letter (no more than 1 page on how your previous projects relate to sensing, processing of EEG/EMG/EOG, ML-based real-time input detection, or AR/VR) Curriculum vitae (PDF) University transcript of records (bachelor's and master's) Contact details of 1–2 academic references Optional: Link to your GitHub profile and/or your portfolio/website The position is open until filled. Reviews begin immediately. Earliest start: Fall 2025. For questions not answered above, contact siplab-recruiting@inf.ethz.ch. Please do not send applications via email. About ETH Zürich ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow. If you apply for this position please say you saw it on Computeroxy

PhD position: Input Detection for Augmented Reality via Learning-based EMG/EOG/EEG Event Detection

100%, Zurich, fixed-term

The Sensing, Interaction & Perception Lab invites applications for a PhD position in Computational Interaction, focusing on sensor-based input detection for Augmented and Mixed Reality. This research combines physiological time series analysis (EEG, EMG, EOG), machine learning, and real-time system design for intelligent interaction systems. The research will contribute to the area of neural input systems and will be related to brain-computer interaction.

Candidates ideally have a background in Computer Science, Electrical Engineering, or Robotics and prior experience with event detection in differential recordings. Additional familiarity with building your own embedded sensing setup is a strong plus. An optimal background for the project would be Electrical Engineering bachelor's (sensing, signal processing) with a more Computer Science-oriented master's (machine learning, time series processing).

Project background

Emerging AR/VR interfaces are limited by the input modalities they rely on and existing input devices have a limited bandwidth: pointing, clicking, typing. The future of Augmented and Mixed Reality systems promises much broader bandwidth for sensing input from a user through brain-computer interaction.

In this project, we aim to explore sensor-based approaches—starting with EEG and later incorporating EMG/EOG—to detect input and user intent. We will explore how sensed differential signals can be leveraged for input, interaction, and adaptive control in MR environments. Central challenges include signal denoising, signal processing, robust event detection, and modeling shifts across sessions and users.

Job description

Develop machine learning pipelines for EEG/EMG/EOG time series processing with a focus on event detection and real-time interaction.
Investigate distribution shifts in physiological data and apply continual learning or transfer learning approaches.
Design and run controlled experiments for data collection in lab and AR environments.
Ideally also devise your own EMG/EOG embedded sensing setup and evaluate edge-AI techniques
Collaborate on building interactive prototypes and validating input systems in AR/VR with others in our interdisciplinary research team.
Disseminate your findings in publications at top-tier venues and open-source your results tools.
Present research findings at academic conferences, workshops, and seminars.

Profile

ETH requirements:

written and spoken fluency in English
an excellent master's degree (MSc., M.Eng. or equivalent) in Computer Science, Electrical Engineering, Robotics, or related field

requirements for the position:

Solid knowledge of machine learning, particularly for time series analysis and event detection
Solid programming skills in C#, C++, or .NET-based languages (in addition to Python)
Experience with differential signals (EEG, EMG, EOG, or similar)
Familiarity with experimental design and empirical validation methods
optional but useful: prior experience with AR/VR and Unity/Unreal

beneficial

Background in online learning or adaptive systems
Familiarity with Unity, AR/VR development, or real-time interfaces
Building your own embedded sensing setup is a strong plus
Experience conducting user studies
Knowledge of biosignal acquisition hardware or even having built your own EEG/EMG/EOG sensing setup
Past experience with brain-computer interaction

Workplace

We offer

We offer an exciting environment and team to study in and work with. Beyond the lab, ETH Zürich has several internationally recognized research groups dedicated to interactive systems, Human-Computer Interaction, AR/VR, health, and machine learning. In our research, we often collaborate with other groups and departments as well as with several other institutions and companies in Switzerland and abroad.

During your PhD, you will have the opportunity to contribute to and collaborate with the ETH AI Center and engage in ETHAR, ETH's Research Hub for Augmented Reality in collaboration with Google XR.

chevron_right Working, teaching and research at ETH Zurich

We value diversity

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Curious? So are we.

Please submit your complete application through the online application portal:

Motivation letter (no more than 1 page on how your previous projects relate to sensing, processing of EEG/EMG/EOG, ML-based real-time input detection, or AR/VR)
Curriculum vitae (PDF)
University transcript of records (bachelor's and master's)
Contact details of 1–2 academic references
Optional: Link to your GitHub profile and/or your portfolio/website

The position is open until filled. Reviews begin immediately. Earliest start: Fall 2025.

For questions not answered above, contact siplab-recruiting@inf.ethz.ch. Please do not send applications via email.

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

If you apply for this position please say you saw it on Computeroxy

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