Wearable sensing in free-living environments to support differential diagnosis and prognosis of Obesity and Hypertension (SDC17)

This PhD project is embedded in Work Package 2 of the ENDOTRAIN network and aims to investigate how endocrine rhythms are affected in patients with obesity and hypertension using real-world, continuous data streams. 
The general project will: 
- Leverage dynamic hormone profiling (e.g., U-RHYTHM) and biosensors for ambulatory assessment in obese and hypertensive individuals. 
- Conduct structured clinical phenotyping including endocrine diagnostics for conditions like primary aldosteronism (PA) and mild autonomous cortisol secretion (MACS). 
- Integrate wearable-derived physiological data (e.g., activity, heart rate, temperature) with endocrine test outcomes to identify diagnostic patterns. 
- Implement pilot trials with biosensor prototypes from partner institutions (e.g., ETH Zurich, Leitwert). 
- Contribute to multimodal datasets feeding into the broader development of digital diagnostic tools in endocrinology. 
 
The portfolio of this specific PhD position will include to:  

• Establish the data collection and monitoring infrastructure using open-source tools with support of IT specialists
• Plan and execute specific wearable sensing studies as per general ENDOTRAIN goals and to support other collaborators in setting up similar studies.
• Gather contextual and patient-reported outcome data (e.g. using structured surveys, as well as spoken or written free text) 
• Develop and validate diagnosis- and prediction algorithms using classical statistics and machine learning tools 

Participants will collaborate closely with other Doctoral Candidates (DC1–DC6) within WP1 and engage in secondments to technical and clinical partners within the consortium. 

Research Fields 

Endocrinology, Digital Health, Medical Sensors, Systems Physiology, Internal Medicine, Machine Learning, Big Data 

Secondments 

- ETH Zurich (CH): Integration and validation of wearable biosensors 
- Leitwert AG (CH): Data synchronization and real-time physiological monitoring 

The Epidemiology, Biostatistics & Prevention Institute is a leading institute in developing and innovating methods for Health Research and Public Health The PhD candidate will be based at Department of Epidemiology and benefit from access methodological support (Statistics, Digital Health), wearable technologies, and extensive international collaborations. The candidate will also collaborate very closely with researchers from the University Hospital Zurich (USZ) Clinic for Endocrinology, Diabetology, and Clinical Nutrition. 

The candidate should work full-time on the project and must not have resided or carried out their main activity (work, studies, etc.) in Switzerland for more than 12 months in the 36 months immediately before their recruitment date.

The student will be enrolled in the structured Epidemiology & Biostatistics PhD programme of the Life Science Zurich Graduate School: 
👉 https://www.lifescience-graduateschool.uzh.ch 
 
Participation in the interdisciplinary training of the ENDOTRAIN network is mandatory, including workshops, retreats, transferable skills courses, and cohort-wide meetings across Europe. 

We are seeking a highly motivated candidate with: 

• A quantitative  Master’s degree (MSc or equivalent) in Statistics, Machine learning, , Biomedical Sciences, , Bioengineering, or a related field 
• Strong interest in translational endocrinology and digital health technologies 
• Willingness to interact with stakeholders (patients, clinicians) 
• Some experience in information- and data management (knowledge of information storage systems/databases are an asset) 
• Excellent programming or data science skills (R, Python) and interest in wearable data analysis are an asset (e.g. time series analysis, machine learning methods for prediction) 
• Excellent command of written and spoken English 
• Good communication skills in English (German is an asset) and capacity for interdisciplinary collaboration  
   

Applicants must fulfil eligibility criteria for Swiss-based PhD positions and be willing to participate in training activities across Europe. 

• Competitive salary according to Swiss National Science Foundation regulations 
• Full social security coverage in Switzerland 
• Travel and secondment budget included 
• Opportunities for international networking, industry exposure, and career development 
• Embedding and opportunities to learn from research groups specialized in Digital Health, Epidemiology, and Biostatistics 

Applications will be run through the University Hospital Zurich (USZ) and University of Zurich (UZH) own recruitment site. 

Call is now closed.

Informal inquiries may be directed to Prof. Milo Puhan (miloalan.puhan@uzh.ch)