Public summary
Join a leading global technology company in Germany for a Master's thesis position focused on ambient sensing to develop digital health biomarkers. This role involves analyzing real-world sensor datasets from senior living environments, conducting literature reviews, creating and validating mathematical models for behavioral health scoring, and documenting findings for internal and scientific use. The thesis requires on-site presence and fluency in English, with a focus on interdisciplinary digital health research.
Location and work setup
- Location
- Renningen
- Remote status
- On-site
- German requirement signal
- No German Required Detected
- Detected job language
- English
Responsibilities
Conduct a comprehensive literature review on ambient sensing for health applications. Preprocess and analyze passive sensor data collected from a multi-home study cohort. Develop, establish, and validate mathematical scoring algorithms to extract meaningful health-related insights. Investigate secondary behavioral biomarkers related to nutrition, appliance use, sleep, and mobility patterns. Validate and demonstrate algorithms in controlled environments, including health-focused living spaces. Document research findings, write code, and prepare presentations and potential scientific publications.
Qualifications
Enrollment in a Master's program in Computer Science, Data Science, Medical Technology, Biomedical Engineering, Physics, or related fields with a strong academic record. Proficiency in Python and common data science libraries such as Pandas, NumPy, and Scikit-learn. Solid understanding of time-series analysis, statistical modeling, or machine learning. Familiarity with smart home systems or sensor data processing is advantageous. Ability to analyze problems methodically, work systematically, and independently manage projects. Fluent English language skills. Availability for on-site work.