PhD Position Sleep, Stress and Arousal in Humans

A World-Class Research Environment at the Intersection of Sleep, Physiology and Health Technology

The Neural Control of Movement Lab at ETH Zurich, Department of Health Sciences and Technology invites exceptional candidates to apply for a PhD position focused on the physiological links between sleep, stress, arousal and health in humans. The project combines mechanistic laboratory experiments with real‑world, home‑based and decentralized phenotyping, using multimodal physiological recordings, mobile health technologies and computational analysis pipelines.

The Neural Control of Movement Lab focuses on understanding how the brain controls behavior and on developing non‑invasive interfaces to measure and modulate brain function during wake and sleep. Within this environment, the PhD student will contribute to a translational research program that aims to understand how daily stress and arousal states shape sleep physiology, recovery and health‑relevant outcomes in real life.

Sleep, stress and arousal are deeply interconnected physiological processes. Persistent stress and heightened arousal can alter the transition into sleep, change nocturnal brain and autonomic activity, and influence recovery, resilience and longer‑term health. Many key mechanisms are still studied either in tightly controlled laboratory settings or through simplified real‑world measures that do not capture the richness of human physiology.

This project addresses that gap by combining mechanistic in‑lab studies with real‑world phenotyping of sleep, stress and arousal in daily life. The goal is to develop rigorous, scalable research workflows that can measure how stress and arousal unfold across the day, how they affect sleep and overnight recovery, and which physiological signatures are most informative for health‑relevant phenotypes.

The project will use multimodal biosignal acquisition, such as pupillometry, sleep EEG, ECG, respiration, wearable and actigraphy data, smartphone‑supported assessments and validated questionnaires, together with advanced signal processing, statistical modelling and machine learning. The PhD student will help implement, coordinate and analyse studies that bridge controlled physiology and ecological, home‑based assessment.

The successful candidate will design, conduct and analyse human studies linking sleep, stress, arousal and autonomic physiology in both laboratory and real‑world settings. A central part of the position will be the implementation of robust research pipelines for mobile and decentralized phenotyping, including data collection workflows, biosignal processing, quality control, synchronization, feature extraction and computational analysis.

The position is ideal for a candidate who wants to combine hands‑on human physiology, sleep research, mobile health methods and strong computational data analysis. Professional software engineers may support parts of the technical backbone, but the PhD student should be able to implement and understand the data flow, work with technical collaborators, implement research‑facing pipelines and take scientific ownership of the physiological data and its interpretation.

• Design and conduct mechanistic laboratory studies and real‑world sleep, stress and arousal studies in human participants
• Acquire and manage multimodal physiological data during wake and sleep such as pupillometry, EEG, ECG, respiration, photoplethysmography, actigraphy, wearable sensor data, smartphone‑based assessments and questionnaires
• Coordinate decentralized and home‑based study workflows, including participant instructions, device logistics, remote monitoring, troubleshooting, documentation and data quality control
• Develop and maintain reproducible analysis pipelines for physiological and behavioural data, including preprocessing, synchronization, artifact handling, feature extraction, visualisation and reporting
• Apply statistical modelling, signal processing and machine learning approaches to identify phenotypes of sleep, stress, arousal and recovery
• Interpret complex physiological data in relation to mechanisms of arousal regulation, autonomic control,…