PhD Position in Epidemiology/Digital Health: Wearable sensing in free-living environments to support differential diagnosis and prognosis of Obesity and Hypertension (SDC16) 80 %
- Unternehmen
- Universität Zürich
- Ort
- Zürich
- Datum
- 21.09.2025
- Referenznummer
- 177908
About the University
The University of Zurich, renowned as Switzerland's largest university, provides a vibrant working environment supported by approximately 10,000 employees and offers diverse professional apprenticeship streams. With a focus on cutting-edge research and exceptional education, UZH invites talented individuals to contribute their expertise.
Your Responsibilities
This PhD project is a key component of Work Package 1 within the ENDOTRAIN network, focusing on the impact of endocrine rhythms in individuals with obesity and hypertension through continuous real-world data analysis. Responsibilities include:
- Establishing a data collection and monitoring infrastructure with open-source tools, supported by IT specialists.
- Planning and executing wearable sensing studies aligned with the goals of ENDOTRAIN, while aiding collaborators in similar study setups.
- Collecting contextual and patient-reported outcome data through structured surveys and free text responses.
- Developing and validating diagnostic and predictive algorithms utilizing classical statistics and machine learning techniques.
Your Profile
We are looking for a highly motivated individual who meets the following criteria:
- A quantitative Master's degree (MSc or equivalent) in Statistics, Machine Learning, Biomedical Sciences, Bioengineering, or a related field.
- A strong interest in translational endocrinology and digital health technologies.
- A willingness to engage with various stakeholders, including patients and clinicians.
- Some familiarity with information and data management; knowledge of information storage systems or databases is advantageous.
- Exceptional programming or data science skills (R, Python) and a keen interest in wearable data analysis, including time series analysis and predictive machine learning methods.
- Fluency in written and spoken English; good communication skills in English and knowledge of German are beneficial.
- A capacity for interdisciplinary collaboration.
Applicants must meet the eligibility requirements for Swiss-based PhD positions and have a willingness to engage in training activities across Europe.
Contact Information
Dr. Marco Kaufmann
Coordinator of PhD program in Epidemiology and Biostatistics