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Master Thesis Ambient Sensing for Digital Health Biomarkers

Renningen, BW, de💼 Full-time🗓 2026-06-30 → 2026-08-01

Core

Develop mathematical scoring algorithms and behavioral health models using passive ambient sensor data to monitor cognitive, metabolic, and physical health decline in senior living environments.

Role type

Master Thesis Researcher (Ambient Sensing & Digital Health)

Builds

Digital biomarkers and behavioral health scoring models

Domain

Digital Health / Ambient Sensing / Senior Living

Deliverable

production ML models

Required skills

Python, time-series analysis, statistical modeling, machine learning, sensor data processing

Preferred skills

Smart home systems (Home Assistant), nutrition tracking, sleep/mobility pattern analysis

Technologies

Pandas, NumPy, Scikit-learn, Home Assistant

Responsibilities

Perform literature review on ambient sensing for health, preprocess and analyze passive sensor data, research and validate mathematical scoring algorithms, investigate secondary behavioral biomarkers, validate algorithms in controlled environments, document findings and evaluate results for presentations/publication

Seniority

Master Thesis Researcher

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