Masterarbeit: Ambient Sensing für digitale Gesundheitsbiomarker (w/m/div.)
Core
Researching and developing ambient sensing algorithms to derive digital health biomarkers from passive smart-home sensor data for monitoring senior citizens' functional independence.
Role type
Master's thesis researcher (ambient sensing & digital health)
Builds
Mathematical scoring algorithms and validated concepts for tracking behavioral health indicators (e.g., mobility, nutrition, sleep patterns) using passive sensor data.
Domain
Digital health / Ambient sensing / Smart Home
Deliverable
production ML models
Required skills
Python, Data Science libraries (Pandas, NumPy, Scikit-learn), Time series analysis, Statistical modeling, Machine Learning
Preferred skills
Smart-Home systems (Home Assistant), Passive sensor data processing
Technologies
Python, Pandas, NumPy, Scikit-learn, Home Assistant
Responsibilities
Analyze real in-home datasets, develop and validate mathematical scoring algorithms, research ambient sensing for health applications, document results and code for potential publication.
Seniority
Master's thesis candidate (6-month duration)