- 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
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PhD Position: Personalized Prediction and Prevention of Dropouts in Digital Biomarker Studies - Zürich, Schweiz - CSS Health Lab
Beschreibung
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:
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