The CP4LS group Computational Physics for Life Science is fascinated by the complex processes and phenomena in the field of biological physics. We are driven by the urge to understand governing mechanisms of these processes with the aim to improve existing and develop novel medical applications.

In particular in the field of medical applications, numerical simulations constitute a powerful and essential tool for testing new hypothesis, provide new insights into fundamental mechanisms and are often able to reveal and assess (potentially harmful) risks of applications. These objectives can be addressed in a rigorous manner without exposing patients to considerable risks.

Our research projects aim to address the following specific

questions:

• How can we exploit latest developments of measurement and imaging techniques for a detailed characterization of the heart?
• What are the governing mechanisms for the onset and perpetuation of cardiac arrhythmia and how can they be controlled in an efficient way?
• How can machine learning algorithms contribute to improve medical applications, e.g. for the development of efficient control strategies for cardiac arrhythmia?

To achieve our goal to promote the development of novel applications in life science, we combine innovative simulation frameworks with state of the art medical measurement techniques and latest machine learning algorithms.