PhD Position: Personalized Prediction and Prevention of Dropouts in Digital Biomarker Studies

PhD Position: Personalized Prediction and Prevention of Dropouts in Digital Biomarker Studies

100%, Zurich, fixed-term

Exciting technological advances in wearables and biosensors rapidly transform how we monitor and manage metabolic health beyond finger pricking and blood picks. Instead, passive, wrist-worn data streams hold massive potential to provide personalized insights into glucose levels and to help inform decisions about diet, exercise, and medication management in everyday life and at scale.

Project background

The CSS Health Lab is a research laboratory at the Centre for Digital Health Interventions, a joint initiative of ETH Zurich and the University of St. Gallen, dedicated to various aspects of digital health and supported by CSS, one of the largest Swiss health insurance companies. Given the increasing health and economic burden of non-communicable diseases, the lab aims to make prevention measurable, actionable, and accountable; and make preventative care successful.

To strengthen the CSS Health Lab, we offer the following position at the School of Medicine at the University of St.Gallen and ETH Zurich under the main supervision of Mia Jovanova, PhD, upcoming Scientific Director of the CSS Health Lab and Postdoctoral Research in Digital Biomarkers for Healthy Longevity, with Prof. Dr. Tobias Kowatsch and Prof. Dr. Florian von Wangenheim being co-supervisors: Research Assistant to obtain a PhD at ETH Zurich.

Job description

You must be eligible for a PhD at ETH Zurich, and you will research the design, development, and evaluation of digital biomarkers in metabolic health with a specific focus on personalized prediction and prevention of dropouts in digital biomarker studies. As part of our team, you take direct project responsibility. You will design protocols for digital biomarker studies and identify and systematically assess intervention components that promote adherence to digital biomarker studies (e.g., based on behavioral economics, health psychology, marketing, and personalized motivational messages delivered by large language model AI chatbots). You will also develop methods to predict and prevent dropouts in such studies. You will work in a highly interdisciplinary team at the intersection of computer science, medicine, and business innovation.

Your profile

You should meet the following requirements:

• A master’s degree in behavioral sciences, with a GPA (Grade Point Average) of at least 5.0 (GPA of 2.0 and better in Germany and Austria) in combination with a strong interest in digital biomarkers
• Strong expertise in machine learning methods, especially with large language models.
• Strong background in experimental research design in digital health and health behavior
• Proficiency in programming languages and familiarity with data visualization techniques and tools for presenting complex data.
• Strong interest in metabolic health, healthy longevity, health economics, and technology-based innovation
• Prior experience in applied research projects, start-ups, or venture capital, as well as prior work experience in the health industry, is advantageous.
• Self-confident appearance and high conceptual and communication skills, especially regarding presenting research results to a broad and interdisciplinary audience
• Profound knowledge (written/oral) in German and English

Your workplace

Your workplace

We offer

ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity and attractive offers and benefits. The average duration for obtaining a Ph.D. is 3.5-4 years. The workplace is divided between Zürich and St. Gallen. A minimum of 2 days (40%) will be in St. Gallen.

We value diversity

Curious? So are we.

We look forward to receiving your online application with the following documents:

• Motivation letter
• Master diploma
• CV

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about CSS Health Lab can be found on our website. Questions regarding the position should be directed to Professor Tobias Kowatsch tkowatsch@ethz.ch, or Giuliana Breu giuliana.breu@mtec.ethz.ch (no applications).

About ETH Zürich

Curious? So are we.

We look forward to receiving your online application with the following documents:

• Motivation letter
• Master diploma
• CV

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about CSS Health Lab can be found on our website. Questions regarding the position should be directed to Professor Tobias Kowatsch tkowatsch@ethz.ch, or Giuliana Breu giuliana.breu@mtec.ethz.ch (no applications).