PhD student in Cybersickness/Virtual Reality: AI-based Detection and Mitigation in Zürich

• Virtual Reality/Unity3D and Interactive Applications with users

• Real-time signal processing of time series (IMU, EEG, EMG, EOG)

• Running user studies through controlled experiments

• User-Interface Adaptation

• processing offline data only or pure machine learning method implementation using datasets

• Research on patients (SCI, stroke patients), rehabilitation

The  is looking for a PhD student in Virtual Reality/Cybersickness at ETH Zurich. We will design and study VR systems that analyze user activity using EEG, EMG, and body-worn IMUs to improve the perception of virtual environments. The objective is to improve user immersion by increasing levels of embodiment and reducing or preventing cybersickness through real-time adaptation of virtual content to mental states.

A major challenge of current VR systems is "cyber sickness", a phenomenon that occurs in over 60% of users. The phenomenon refers to the set of deleterious symptoms that can occur after more or less prolonged use of virtual reality systems. Less severe, depending on personal characteristics, users can suffer from breaks in presence and immersion due to anomalies in rendering and interaction, which can lead to a bad feeling of embodiment in their virtual avatars. All these cases severely affect the user experience to the detriment of pleasant interactions and thus the success of immersive computing. Therefore, research on these phenomena is required to tailor interaction to users' physiological reactions and adapt immersive environments in real time.

Goals

• identify, characterize, and detect neurophysiological and behavioral markers associated with cybersickness
• verify these markers in participant experiments in controlled studies
• develop real-time adaptations for immersive environments in VR in response to symptom development

The work will comprise methodological and practical aspects. We will evaluate our systems end-to-end in empirical settings with end users.

ETH requirements:

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

requirements for the position:

• experience in signal processing (e.g., ECG, EEG, EMG, EOG)
• experience with VR or AR, Unity/C# (or comparable 3D programming)
• experience conducting user evaluations or controlled experiments
• strong interpersonal and communication skills

Prior experience in analyzing collected EEG data is highly appreciated.

We offer an exciting environment and to study in and work with. Beyond the lab, ETH Zürich has several internationally recognized research groups dedicated to signal processing, neurophysiological computing, machine learning, and physiological computing. We also collaborate with several other institutions and companies in Switzerland and abroad.