PhD position Personalized Oncology

PhD position on the Inverse Biophysical Modeling and Machine Learning in Personalized Oncology

Technical University of Munich, Germany 

Project description: Understanding the dynamics of brain tumor progression is essential for optimal treatment planning. Cast in a mathematical formulation, it can be viewed as an evaluation of a system of partial differential equations, wherein the underlying physiological processes that govern the growth of the tumor, such as diffusion and proliferation of tumor cells, are considered. To personalize the model, i.e. find a relevant set of parameters, with respect to the tumor dynamics of a particular patient, the model can be informed from empirical data, e.g., medical images obtained from different diagnostic modalities, such as magnetic-resonance imaging (MRI) or positron-emission tomography (PET). Recently, we performed proof-of-concept studies with deep-learning based personalization techniques. The goal of the PhD project is to pave the way between the existing or potentially newly developed personalization methodologies and clinical practice.