Biomedical Application:

The core application is respiratory gas analysis for early-stage disease diagnostics and therapy monitoring. By leveraging Raman spectroscopy, you will work towards analyzing gaseous biomarkers.

Challenges and Methods:

Raman spectroscopy is an extremely versatile and emerging technique for multigas sensing. Your mission will be to develop new methods under the optimal experimental design framework.

Data Source:

You'll analyze Raman spectroscopic data with the Biophotonics – Biomedical Engineering Group. We are at the forefront of developing advanced laser spectroscopic techniques for personalized medicine and therapy monitoring.

Prerequisites:

• Strong foundation in statistical signal processing and machine learning: Essential for developing and refining the complex algorithms required.

• Programming skills: Proficiency in Python, R, or C++ is crucial for implementing the algorithms efficiently.

• Interest in advanced laser spectroscopic techniques and their application for biomedical sensing

• Motivation and interest: A high level of enthusiasm for developing advanced methods and working with real biomedical data is key to success in this project.

Why This Project?

This project provides a distinctive chance to make significant contributions to a critical field of biomedical engineering. Under the guidance of the Robust Data Science Group and the Biophotonics – Biomedical Engineering Group, you will have the opportunity to advance your expertise in machine learning, signal processing, and biomedical engineering. By creating cutting-edge techniques for Raman spectroscopy based multigas analysis, you will play a leading role in the evolution of breath analysis, influencing the future of healthcare.

How to Apply?

• Please send an E-Mail to michael.muma@tu-darmstadt.de with your CV and transcript.