PhD Position on Sleep, Stress and Arousal in Humans

The successful candidate will design, conduct and analyze 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. Your work will include: 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 behavioral data, including preprocessing, synchronization, artifact handling, feature extraction, visualization 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, sleep physiology and health-relevant outcomes Work closely with researchers, engineers, clinicians, students and external collaborators to connect experimental design, data infrastructure and scientific analysis Disseminate findings through scientific publications, conference presentations and contributions to larger translational research initiatives

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 Department of Health Sciences and Technology at ETH Zurich unites researchers across neuroscience, biomedical engineering, movement science, nutrition, physiology and medicine. It offers an interdisciplinary environment for research at the interface of human biology, technology and clinical translation. 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. More than 30,000 people from over 120 countries find ETH Zurich to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet connected all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

• A Master's degree (or near completion), in biomedical engineering, medical engineering, medical informatics, computational neuroscience, data science, or a closely related field, with demonstrated quantitative and programming skills

• Strong programming skills in Python, MATLAB, R, or comparable languages are essential, together with experience writing clean, well-documented, and reproducible analysis code

• Strong skills in data analysis, statistics, signal processing, computational modelling, machine learning or artificial intelligence for complex physiological or behavioral data

• Experience with physiological data acquisition and analysis, ideally including sleep EEG, ECG, respiration, photoplethysmography, actigraphy, wearable sensors or other multimodal biosignal time series

• A solid understanding of human physiology and strong motivation to work on sleep, stress, arousal, autonomic regulation, recovery and health-relevant phenotyping

• Experience designing or conducting human research studies, including experimental protocols, participant-facing work, ethics-aware procedures, documentation and quality control

• Ability to build and manage structured research pipelines, including data ingestion, preprocessing, synchronization, artifact handling, feature extraction, validation, visualization and reporting

• Capacity to coordinate real-world, home-based or decentralized studies with high reliability, including device workflows, participant instructions, troubleshooting and data integrity checks

• A highly structured, detail-oriented and reliable working style, with excellent documentation habits, careful follow-through and respect for sensitive human research data

• Scientific curiosity, intellectual independence, strong work ethic, problem-solving ability and enthusiasm for interdisciplinary research at the interface of physiology, technology and health

• Excellent communication skills and the ability to collaborate with researchers, engineers, clinicians, students, study staff, technical partners and human participants

• Fluency in English

• German language skills are an advantage, especially for participant-facing work