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# Master Thesis Ambient Sensing for Digital Health Biomarkers

- **Company:** Robert Bosch GmbH
- **Location:** Magstadt, Germany
- **Contract:** Temporary contract
- **Skills:** EHealth, Python (Programming Language), Machine Learning, NumPy, Pandas, Scikit Learn, Information Technology
- **Published:** July 2, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=681a10128b74b946

## About the Role

* Education: Master studies in the field of Computer Science, Data Science, Medical Technology, Biomedical Engineering, Physics, or comparable with a good academic record
 * Experience and Knowledge: proficient in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn); solid understanding of time-series analysis, statistical modeling, or machine learning; familiarity with smart home systems (e.g., Home Assistant) or sensor data processing is a plus
 * Personality and Working Practice: you excel at analyzing problems methodically, structuring your work systematically, while independently driving projects toward key goals
 * Work Routine: your on-site presence is required
 * Enthusiasm: you show great enthusiasm for interdisciplinary digital health research, and enjoy presenting complex results
 * Languages: fluent in English

## Description

Passive-ambient smart home sensors offer a unique, privacy-preserving opportunity to continuously monitor health and functional independence in senior living. By analyzing subtle patterns in daily life (e.g., appliance use, room transitions, door movements), we can derive digital biomarkers to act as leading indicators for cognitive, metabolic, or physical health decline.

 * As part of our research team, you will dive into ambient sensing, analyze real-world in-home datasets, and help develop cutting-edge behavioral health scoring models.
 * You will perform a comprehensive literature review on ambient sension for health applications.
 * Furthermore, you will preprocess and analyze passive sensor data (activity, presence, power usage) collected from our multi-home study cohort.
 * You will research, establish, and validate mathematical scoring algorithms that condense meaningful insights from the data.
 * Additionally, you will investigate secondary behavioral biomarkers, exploring concepts like nutrition/appliance tracking and sleep/mobility patterns.
 * Moreover, you will validate and showcase your algorithms in controlled environments, including inside a health-centric tiny home.
 * Finally, you will document research findings, code, and evaluate results for internal presentations and potential scientific publication.


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