We invite motivated Master’s students to participate in an important and timely research project investigating whether, and to what degree, digital biomarkers can predict diabetes outcomes. As digital health tools continue to advance, understanding how data from wearables, smartphones, and other technologies can help forecast diabetes outcomes is critical for improving early detection and personalized care.

Project Overview

The student will conduct a systematic review of the current literature to assess the potential of digital biomarkers—such as those derived from wearables, mobile apps, or other digital health devices—to predict diabetes outcomes. This research will identify key trends, opportunities, and gaps in the field, providing valuable insights that could inform clinical practice and future research. The thesis will be part of our larger effort to harness technology for better diabetes management and prevention.

Key Responsibilities

• Conduct a systematic review of the literature on digital biomarkers and their role in predicting diabetes outcomes.
• Analyze the accuracy, utility, and limitations of these biomarkers in various clinical settings.
• Compare findings across different types of digital digital biomarkers and diabetes-related outcomes (e.g., HbA1c levels, hypoglycemia, disease progression).
• Collaborate with your thesis supervisor and our CSS Health Lab research team to ensure rigorous analysis and impactful contributions to the field.

Who Should Apply?

This project is ideal for students interested in digital health, data science, health informatics, or related fields. Strong analytical skills, attention to detail, and a passion for exploring the intersection of technology and healthcare are essential. Interested students should submit a brief statement of interest and their CV to Dr. Mia Jovanova (mia.jovanova@unisg.ch). We encourage applicants from diverse academic backgrounds to apply.

This research offers a unique opportunity to shape the future of diabetes care by advancing our understanding of how digital biomarkers can support earlier interventions and better health outcomes. Join us in shaping the future of personalized healthcare!