As part of a dynamic research team at the Institute of Occupational Medicine, you will work on a master thesis project that combines data-driven health research with cutting-edge AI techniques.
Project Overview
This project focuses on developing agentic AI pipelines for integrated analysis of continuous glucose monitoring time series, meal photographs, and light exposure data collected over 10 days in everyday life of healthy young and older adults. The dataset comprises ten consecutive days of data from 60 healthy participants, including 30 younger and 30 older adults.
Aims and Objectives
* Develop agentic AI pipelines for integrated analysis of CGM time series, meal photographs, and light exposure data
* Explore how modern agent-based AI frameworks can autonomously generate annotations, perform time-aware analyses, and support hypothesis generation in circadian-metabolic research
Research Background
Circadian misalignment is increasingly recognized as a key pathophysiological driver of metabolic diseases, especially in populations exposed to night shift work. Recent advances in wearable sensor technology allow for highly granular 24-hour data acquisition in real-world settings.
Required Skills and Qualifications
To be considered for this position, candidates should possess a strong background in computer science, machine learning, or a related field, along with excellent programming skills and experience working with large datasets. Additionally, proficiency in Python and familiarity with popular libraries such as TensorFlow and PyTorch are highly desirable.
Benefits
This master thesis project offers the opportunity to work on a cutting-edge topic, develop innovative solutions, and contribute to the advancement of data-driven health research. Furthermore, successful completion of the project will provide valuable experience and a strong portfolio of accomplishments to enhance future career prospects.
Others
The Institute of Occupational Medicine provides a collaborative and supportive research environment, fostering the development of skills and knowledge in data analysis, machine learning, and AI. This project aligns with the institute's mission to improve human health and well-being through interdisciplinary research and innovation.